Search Results

Scene Understanding, within artificial intelligence research, endeavours to impart to computers the capacity to perceive visual situations like humans. It involves interpreting and comprehending the elements within an image or scene, mirroring human cognitive processes. At its core, Scene Understanding strives to empower machines to perceive, comprehend, and rationalise the visual realm, enabling them to undertake suitable actions based on their interpretation of the scene. By leaning into the capabilities of In-Store Scene Understanding (ISSU) technology with innovative solutions from Neurolabs, Consumer Packaged Goods (CPG) and retail businesses can use ISSU to gain comprehensive insights into their operational dynamics, customer behaviour, and competitive strategies within physical retail spaces. What Is In-Store Scene Understanding (ISSU) Technology? ISSU, or In-Store Scene Understanding, transforms how CPG brands boost sales and manage products. It offers a full view of what's happening in stores, showing both a brand's and competitors' activities. This is fundamental when it comes to retail execution. For CPG brands, the battleground is the retail environment, where products vie for attention and consumer loyalty is won or lost in a matter of seconds. Stellar retail execution ensures that products are available for consumers and that they are strategically placed but also presented in an engaging and appealing manner. From eye-catching displays and prominent shelf positions to impeccable inventory management, every facet of retail execution influences the consumer's purchasing decision. In an industry where competition is fierce and consumer expectations are ever-evolving, the art of retail execution emerges as a crucial differentiator, driving the success and growth of CPG businesses. Unlike older methods that rely only on real-world data, ISSU uses synthetic data to understand visuals better. Ultimately, this replaces the outdated constraints of 'Planogram compliance,' liberating brands from their exclusive product focus. It offers an expansive perspective on the retail environment, encompassing not only the broader competitive space but also extending to the complementary ongoing promotional activities within the store. Streamlining Retail Operations With ZIA Nerolabs ZIA (Zero Image Annotations) transforms Consumer Packaged Goods image recognition by eradicating manual annotations and reliance on real data. Leveraging 3D assets and virtual scenes of CPG products, ZIA swiftly delivers precise product detection and in-store insights. This innovative approach offers faster, more accurate results at a reduced cost compared to other solutions. Pioneering Retail Success through Advanced Image Insights In today's fast-paced retail landscape, staying ahead means embracing innovative technologies that streamline operations and offer a competitive edge. Enter ZIA Capture, our transformative onboarding tool revolutionising the SKU (Stock Keeping Unit) and POP (Point of Purchase) material integration process. Its cutting-edge capabilities reduce time and costs and provide invaluable insights into competitor catalogues. The breakthrough lies in resolving the long-standing challenge that has been holding you back: catalogue management. This is achieved through effective solutions, such as: Universal Artwork Approach: Bid farewell to artwork concerns. Generate precise 3D models swiftly, enabling rapid onboarding without specific artwork. Moreover, delve into your competitors' catalogues, leveraging competitor insights effortlessly. Automated Barcode Recognition: Simplifying SKU addition, ZIA Capture automatically uploads barcodes. Manual input of EAN/UPCs is eliminated, enabling seamless product and category search and reporting within your catalogue. Efficient Onboarding: ZIA Capture accelerates the entire catalogue onboarding process, delivering a synthetic IR training model ready for deployment within a day. Achieve over 96% accuracy from the start, onboarding 50 - 100 SKUs in under two hours, with the potential for even faster future processes. Embracing ZIA Capture in retail operations marks a significant stride toward efficiency, cost-effectiveness, and market agility. Using ZIA for SKU and POP Onboarding ZIA Capture streamlines the SKU and POP material onboarding process, reducing time and costs significantly. Several key advantages drive this streamlined experience: Efficiency: Streamlined onboarding processes significantly reduce the time and effort required to add new products to the catalogue. This efficiency translates to quicker time to market, enabling faster responses to market demands and trends. Cost Savings: Businesses can reduce operational costs associated with manual data collection by automating tasks like barcode recognition and universal artwork creation. The faster onboarding process also means quicker time to market, potentially increasing revenue streams. Competitive Edge: Accessing competitor insights by onboarding their catalogues allows businesses to swiftly understand market trends and competitor product positioning. This valuable information aids in making informed decisions and devising competitive strategies. Accuracy and Consistency: ZIA Capture's automated processes enhance accuracy and consistency in product data management. This ensures the catalogue is up-to-date, minimising errors and discrepancies, ultimately improving customer satisfaction. Adaptability and Scalability: The rapid onboarding capabilities of ZIA Capture facilitate the easy addition of new products and scale-up of the catalogue. This adaptability is crucial in keeping up with industry changes and customer demands. By leveraging this innovative technology, businesses can pave the way for streamlined operations, better-informed strategies, and sustained competitiveness in the retail landscape. A Perfect Partnership: Generative AI & ISSU As demonstrated above, ISSU provides valuable insights for various important industry adaptations. However, the key lies in leveraging these insights effectively to get the best results possible. Generative AI simplifies this process, enhancing productivity. An AI assistant can provide instant access to valuable knowledge and enhancements when paired with a well-organised catalogue. Introducing, ChatGPG ChatCPG, our AI tool, empowers CPG brands and Field Marketing Agencies (FMAs) to achieve Perfect Store execution effortlessly. Instead of the hassle of sifting through numerous spreadsheets and dashboards for information like compliance percentages in specific locations, you can ask ChatCPG the same question and receive an accurate answer within seconds. ChatCPG utilises cutting-edge synthetic IR technology, leveraging data sourced from ZIA to analyse crucial shelf Key Performance Indicators (KPIs) such as out-of-stock items, planogram compliance, share of shelf, and shelf availability. For example, if you ask about specific details like the availability of Pepsi products in a specific branch in Waitrose, Surrey, ChatCPG swiftly scans your data and provides an accurate response within seconds. How ChatGPG Helps ChatCPG elevates ISSU's capabilities by enabling effortless verbalisation of the in-store scene. It goes beyond mere shelf-level inquiries, allowing exploration of the broader store environment and competitor landscape. By asking strategic questions, you gain insights into the surroundings of your products, empowering informed strategies without guesswork. You can use the technology for important, instant insights on things such as: Shelf compliance Product availability Price Analysis Competitor analysis Promotional display compliance Quality control Inventory visibility With each inquiry, ChatCPG crafts a detailed and precise snapshot, presenting a substantial competitive edge that, when utilised, fosters exponential growth. And the possibilities don't end there! By integrating insights from ZIA with other data sources (such as sales orders and historical sales performance), ChatCPG can seamlessly guide your retail execution team with actionable suggestions. Transition from capturing a few photos to gaining actionable insights in a matter of seconds! Ready To Embrace ISSU? Partner With Neurolabs & Transform Your Business Here at Neurolabs, pioneering ISSU in the retail industry is at the forefront of what we do. Our technology stands as a catalyst, strategically propelling numerous retail companies towards growth. Leveraging ISSU, we've empowered businesses to identify weaknesses, amplify strengths, and chart a course for success. To discover how our innovative solutions can drive your business forward, reach out to us today. We're eager to collaborate and propel your journey towards retail excellence. At Neurolabs, we are revolutionising in-store retail performance with our advanced image recognition technology, ZIA. Our cutting-edge technology enables retailers, field marketing agencies and CPG brands to optimise store execution, enhance the customer experience, and boost revenue as we build the most comprehensive 3D asset library for product recognition in the CPG industry.

Greetings to All, With the end of the year on the horizon, it is time to take a deep breath and look back on a year that was as unpredictable as it was rich in learning experiences. This year, we've experienced both the positives of the remarkable advancements in AI and the challenges of a rough financial climate. Generative Pre-Trained Transformers (GPTs), and specifically ChatGPT, have lowered the entry barrier for AI adoption while displaying an impressive array of skills. The speed of adoption is mind-blowing - at my local barbershop, there’s a wall of pictures with hairstyles made with “GenAI”. This technology is bound to touch every industry in the shortest amount of time. At the same time, we've faced strong economic headwinds – rising interest rates and a slowing economy have touched us all. Some of the signs were closer to home than others: one of our investors closed a 1/10th of the investments they did the year prior, and in December, the law firm we partner with is handling three separate company closures. To call it a rollercoaster would be an understatement. The Dawn of Specialised AI Solutions As we navigate this sea of change, we recognise the long road ahead to AI commoditisation, and that the adoption curve is just at its beginning. Off-the-shelf AI solutions that meet the demanding needs of Consumer Packaged Goods (CPG) brands are far away from today’s reality. This brings us to a common question: How do we compare to giants like Google or Microsoft? Their cloud offerings are growing every year, and with the advent of Large Language Models, one can only wonder what’s the ceiling for what AI can do. While certain aspects like infrastructure and algorithms are becoming more accessible, the true value lies in the specifics of the industry - the nitty-gritty details that define success in the CPG space. This dichotomy reminds me of Archilochus' fox-hedgehog parable: 'The fox knows many things, but the hedgehog knows one big thing.' In the realm of CPG, it's the experts (hedgehogs) who thrive amidst the generalists (foxes). Our ability to focus on the distinction lies in two key areas: catalogue specificity and technology robustness. For instance, while Microsoft might offer the latest GPT-4 Vision models integrated into their cloud offering, they aren’t getting anywhere near the level of specificity required to understand a complex retail scenario. Neurolabs’ strength is our up-to-date product catalogue matched with the latest AI algorithms - a level of specificity and robustness that, in my opinion, neither Google through their retail-specific Product Recogniser solution nor Microsoft with Cloud for Retail can currently match. Looking Ahead: From Shelf Visibility to Actionable Insights As we move into 2024, our vision is clear. We will push the boundaries of what AI can offer in the CPG space. Beyond offering visibility on the shelf execution and supply chain, AI models can deliver actionable insights to the field agent, marketing manager, and the head of sales alike. Throughout this year, I often resonated with the concept of the 'Innovator’s Dilemma' - a successful company will struggle to adapt to new technologies because they are focused solely on refining their existing products. Throughout the year, it became evident that this challenge is omnipresent in Retail and CPG sectors. The urgent need for AI and automation adoption is recognised quickly by leaders in the space, as it is evident that what used to work yesterday will no longer work tomorrow. Labour shortages and the demand for more efficient supply chains will force the adoption to happen, even in an industry often called a laggard. In closing, I extend my deepest gratitude to every member of the Neurolabs team and our patient shareholders. Your dedication, creativity, and hard work have been the driving force behind Neurolabs closing the year with 3x the revenue that we started with. Together, we are not bystanders in the AI revolution; we are at its forefront, shaping the future with a focus on our target market - the Consumer Packaged Goods space. To our clients, I thank you for putting your trust in us from an early stage. It’s a long journey ahead, and it’s a privilege to have all of you supporting us as we navigate these uncharted waters. It is your insights and feedback that push us to innovate and strive for excellence. Wishing you all a prosperous and groundbreaking new year. Warm regards, Paul Pop CEO, Neurolabs

We created Neurolabs to solve the problem of high costs and manual labour involved in annotating everyday objects for image recognition (IR) in machine learning recognisers. Our breakthrough came from recognising real-world objects with high accuracy by training computer models with millions of synthetic scene versions and simulating real-world conditions. We swiftly recognised that applying digital twins enabled by Synthetic Image Recognition (SIR) could be used beyond object recognition. These digital replicas proved versatile, extending their utility from integration into virtual environments to creating photorealistic 3D images for e-commerce platforms. The Grocery and Consumer Packaged Goods (CPG) sectors were among the early adopters, captivated by the transformative potential of our technology. Working with leading Global brands, we developed the idea of creating digital twins that mirrored a product's lifecycle. By having access to digital twins across the product's lifecycle, clients could see how they could materially improve their operations. In this blog post, we will outline the lifecycle of a typical product and explore how a CPG can benefit and improve its operations across that lifecycle, from manufacturing to recycling. Digital Twins Digital Twins were first voiced in 1991 in a publication by Gelernter called Mirror Worlds, but their first known application in manufacturing was by Dr. Grieves in 2002. The first applications were creating simulations to model an object's behaviour before manufacturing a prototype. Still, with the rise of the Internet of Things (IoT), applications rapidly expanded to measuring the output of sensors on real-world objects and managing the real world. The traditional view of a "Digital Twin" refers to a digital representation or virtual counterpart of a physical object, system, or process. A “twin” is a digital model replicating the real-world entity in a digital environment, allowing for real-time monitoring, analysis, and simulation. The concept involves creating a dynamic and interconnected digital replica that mirrors the physical entity's characteristics, behaviour, and changes over time. By collecting and integrating data from sensors, IoT devices, and other sources, Digital Twins enable organisations to gain insights into the performance, condition, and status of the corresponding physical object or system. At Neurolabs, we believe that, like many advanced users of Digital Twins such as Rolls Royce, Digital Twins are multi-layered and are of most value when context is included in the twin. What do we mean by context? A context could be a process that is applied to an object. Commonly, one would think of manufacturing, but at Neurolabs, we would, for example, add the context of Marketing. Imagine a SIR-enabled sensor identifying a promotional version of product packaging that is now being manufactured and alerting the Marketing team to initiate the planned marketing activities. This version of the digital twin exists in parallel with the manufacturing “twin” that doesn’t care about the packaging version. The manufacturing twin's purpose is to monitor the weight, shape, and volume to ensure the manufacturing line is running smoothly. In both cases, there is a “model” of the packaging, the latter recognising both special “promotional” and “regular” as the same item. Similarly, at “end of life”, another version of the twin would be the deformed packaging that allows SIR-sensors to differentiate between recyclable products and general waste. Historically, it was expensive to create digital twins, so the "twinning" was initially limited to industries with high-value products. However, more and more companies are using the technique to improve their businesses. At Neurolabs, we believe the time is already upon us to apply the concept to everyday products on grocery store shelves everywhere. Our digital twin approach has multiple attributes, such as: Fully rendered packaging including deformed packaging Unique ID of each product version Nutritional information Weight, dimensions, volume, location Inclusion of EAN/UPC barcodes This wealth of data provides comprehensive insights across all aspects of CPG’s operations. By embracing the multi-layered nature of Digital Twins and integrating context, we aim to redefine their application, offering a transformative impact on the retail industry. What are CPG's priorities? Many consulting organisations have surveyed CPGs and synthesised what they consider essential to the success of their business. Those essentials have stayed the same over time. They are to manufacture, distribute, sell, and increasingly sustainably recycle their products with minimal waste of raw materials at a healthy profit. However, in an increasingly competitive market, the difference between those that execute well and those that do not is stark. McKinsey reports that while every company "leaks" value at various stages in their process, those who follow through and sustain their initiatives retain 2.0x the value compared to those whose "peter out." In recent studies, both McKinsey and Salesforce highlight that achieving step changes in: Functional Excellence Adapting to the Modern Consumer Increasing Enterprise Resilience are the keys to staying ahead. In short, it is all about persistently transforming business processes to meet market challenges. Achieving this transformation is extremely difficult without data about the product at every process step. At present, gaps in data across the life cycle mean that collaboration and process improvements are hindered or even unimplementable. To illustrate how access to that missing information can enable change, improve collaboration and increase value, we looked at the life cycle of a product (SKU) and where our capability could unlock the bottlenecks. Manufacturing Whilst we have some experience with products before packaging, see our work with Sagra Technologies, SIR shines post-packaging. The technology is straightforwardly used to: Verify labels to ensure a product does not leave manufacturing with incorrect labelling, such as wrong batch and expiry dates, avoiding expensive recalls in the supply chain. In the US, the Food Marketing Institute found that recalls cost companies an average of $10 million in direct costs alone. Identifying specific promotional packaging in the manufacturing process, enabling collaboration with marketing to trigger campaign execution precisely. According to Salesforce research, 87% of CPGs spend between 20% and 50% of gross revenue on promotion, so getting the timing right is revolutionary. Logistics As we now have fully rendered models of our product, we can start to do clever scheduling of promotions from within automated warehouses. In an automated warehouse, a picking robot such as those used by Ocado could be used to choose a specific product version to send to a particular post-code or for timed delivery to coincide with external trade promotions or digital marketing. Similarly, if a specific product is in a local quick commerce centre, SIR-enabled picking devices can pick a precise product with the same benefits. SIR-enabled logistics makes it straightforward to track exact products arriving at goods inwards and equally at goods out, something a barcode cannot replicate. Further, as mentioned in the manufacturing section, if a product recall is initiated, those robots or SIR-enabled picking devices could automatically remove the product from the warehouse stock. Retail Once a specific product arrives at a retail location, SIR begins to shine. To set some context, Trade promotion, according to McKinsey, is up to 20% of a CPG’s revenue, and by extension, poor delivery of the process from budgeting through execution to evaluation has a material impact on the bottom line. As the marketing team has been notified that a particular variant is now in the logistics chain, one can more precisely coordinate digital marketing campaigns to drive footfall, making trade promotions more effective, a capability unheard of previously. With this knowledge, field teams can be timetabled to encourage compliance using SIR-enabled devices. Since compliance has been estimated to be 55% by the Promotion Optimisation Institute, gains in compliance will revolutionise the industry. For all the focus of a CPG to improve promotion effectiveness, a customer can only buy what is on the shelf! Given that it’s known that 65% of shoppers don't buy the product when presented with an out-of-stock (OOS), it is imperative that shelves for those items, which, as a CPG, you have paid to be promoted, are replenished promptly. With cameras (fixed or mobile) equipped with SIR, OOS can be recognised in real-time, and rapid action can be taken. With the stress driven by the cost of living crisis, Grocers are experiencing far higher shrinkage levels. With the rise of self-scan, a typical behaviour is to scan the barcode of a less expensive item and place a more expensive item in the cart. “Swapping” has now extended to produce. With SIR recognition cameras placed above weight scales, shoppers can be nudged to identify the item correctly. The same capability for packaged goods can be enabled at self-checkout, reducing shrinkage. Continuing on the theme of loss, another increasing cause of revenue loss is the rise of counterfeiting. Initially, counterfeits were confined to high-value items such as designer clothing, but counterfeits are increasingly popping up at lower price points. Counterfeit premium alcohol is sufficiently widespread to account for losses totalling $500-$700m/pa. Often, the counterfeits have subtlety different packaging, with SIR-detection embedded watermarks, fakes can be detected quickly and cheaply. It is an urban legend that Cashiers at certain supermarkets are very quick at processing a shop. The cashier's skill is to orient a product so the till immediately scans a barcode. With SIR-enabled tills, orientation isn’t a problem, enabling more rapid checkouts with less staff per open lane. In the Home According to Wikipedia, LG released the first Internet-connected fridge in 2000, which used cameras to “know” what was inside. However, since then, with the rise of the smartphone, people now routinely scan a product to capture its nutritional value in a calorie-counting app or to add it to an online shopping order. With SIR on those different apps, CPGs could pay to receive the information and build up a “profile” of a household or pay to or offer a promotion to incent the shopper to add a substitute to the order. Recycling At the end of a product's lifecycle, there is almost always waste. CPGs, to keep perishable items fresh, have used packaging that continues to contribute to the vast mountains of waste plastic dumped into landfills. A crucial part of recycling is sorting the waste at the first disposal point. Not too long ago, humans were the only sorting devices. However, with the increasing rise in smart bins, beginning in public spaces, SIR-enabled bins will soon efficiently sort waste with models supplied by CPGs as a public service. The data collected enables the tracking of where and what can be recycled. Sources: Secrets to implementation success, MkKinsey 2016 Operations as a competitive advantage in a disruptive environment, McKinsey 2016 Consumer Goods Industry Insights Report, Salesforce 2023 At Neurolabs, we are revolutionising in-store retail performance with our advanced image recognition technology, ZIA. Our cutting-edge technology enables retailers, field marketing agencies and CPG brands to optimise store execution, enhance the customer experience, and boost revenue as we build the most comprehensive 3D asset library for product recognition in the CPG industry.

Today marks a momentous occasion for Neurolabs as we proudly announce our win as the Best Retail Computer Vision Technology Company at the SME Scottish Enterprise Awards 2023. Hosted by SME News, these prestigious awards shine a spotlight on exceptional achievements in the Scottish business landscape, recognising innovation, excellence, and contributions to various industries. At Neurolabs, we are proud to be recognised for our innovative solutions within the retail automation industry. Our team of experienced professionals, with master's degrees and PhDs in computer science and math, is dedicated to providing cutting-edge services that revolutionise the Consumer Packaged Goods (CPG) industry. Through the use of synthetic image recognition technology, including digital twins and virtual environment training, we are empowering businesses to enhance their image recognition capabilities for retail execution. Serving industry giants such as P&G, Coca-Cola, Nestlé, and JTI demonstrate the trust that the world's leading companies place in our state-of-the-art technology. Our mission at Neurolabs is to democratise computer vision technology within the CPG sector, simplifying automation and reducing waste. We believe in making these tools accessible to a broad range of users, without the need for specialised skills. By offering innovative and inclusive R&D advancements, we are driving positive change in the industry. The Scottish market has been particularly receptive to our innovations, reflecting the national impetus towards technological advancement in retail. With our roots in the University of Edinburgh and the support of the Scottish government, Scotland has been an exceptional base for our R&D and operational activities. Our success can be attributed to our flat hierarchical structure, fostering autonomy and a strong team dynamic. We value community spirit, respect, reliability, and authenticity. It is our dedicated and enthusiastic team that turns our groundbreaking conceptualisations into realities. Looking ahead, our collaboration with the University of Edinburgh and the South Korean project team at UNIST along with the impending launch of our flagship product, ZIA Capture, will solidify our position as a beacon of R&D innovation and revolutionise supply chain visibility. Receiving this award is a testament to our achievements and innovation within the field. We are honoured to be recognised and will continue to push boundaries, shaping the future of retail automation. To learn more about our award-winning, next-generation solutions, book a demo with our expert team today. At Neurolabs, we are revolutionising in-store retail performance with our advanced image recognition technology, ZIA. Our cutting-edge technology enables retailers, field marketing agencies and CPG brands to optimise store execution, enhance the customer experience, and boost revenue as we build the most comprehensive 3D asset library for product recognition in the CPG industry.

Synthetic Computer Vision (SCV) is an emerging technology that combines computer-generated imagery (CGI) and machine learning to train models in understanding visual information. In SCV, the emphasis is on employing artificially generated data instead of solely relying on real-world data. This approach has several benefits compared to traditional computer vision methods: Speed of Execution: Synthetic data can be generated in a fraction of the time at scale. Scalability: SCV can be used to generate synthetic data for virtually any scenario. It also eliminates the time and cost associated with human labelling in traditional image recognition (IR), often known as ‘Human in the loop’. Accuracy: SCV models can be trained using synthetic data, to achieve a higher level of diverse data sets. This gives it superior accuracy than models trained on real-world data because it’s not limited by the constraints of the real world. Synthetic data can be generated using a much wider range of lighting conditions, backgrounds and object placements which is particularly important in challenging environments such as pharmacies and in specialty retail. Harnessing its competitive advantages, SCV finds diverse applications across a spectrum of industries, including: Revolutionising Transportation Fuelling the evolution of self-driving cars, SCV is instrumental in training models to adeptly recognise and respond to a myriad of scenarios - be it identifying pedestrians, cyclists, other vehicles, or deciphering traffic signs. Advancing Healthcare In the realm of medical imaging, SCV takes centre stage, empowering models to discern and diagnose diseases with precision, tackling challenges in areas such as cancer and heart disease. Empowering Robotics SCV serves as the backbone for training robots, enabling them to navigate and seamlessly interact with the dynamic environment surrounding them. Enhancing Manufacturing Within the manufacturing landscape, SCV plays a crucial role by training quality control models to detect imperfections and defects in products, ensuring a higher standard of manufacturing excellence. Transforming Retail In the retail sector, SCV is a game-changer, training models to meticulously track inventory, identify out-of-stock items, and strategically optimise product placement for an elevated shopping experience. Elevating Agriculture Practices SCV extends its impact to agriculture, where it trains models to detect and combat pests and diseases in crops, while also monitoring and enhancing overall crop growth. In transforming retail execution through SCV, we've had the privilege of witnessing our CPG clients achieve remarkable success. A noteworthy example is our collaborative journey with Sagra Technologies, where their Image Recognition capabilities were significantly enhanced. Together, we achieved the following milestones for Sagra Technologies: Facilitated a swift transition from onboarding to project delivery in just 7 days. Seamlessly integrated with their SFA System, boosting overall operational efficiency. Powerful image recognition able to provide distinctions between nearly identical SKUs. For Consumer Packaged Good (CPGs) brands, grappling with challenges in data and technology, SCV emerges as a transformative ally, offering the key to overcoming these hurdles. CPGs are being held back from competing for a variety of reasons but two of the most significant are a lack of adequate insights and technology. Let’s explore how SCV is proving instrumental in effectively addressing and resolving both of these critical challenges. Adequate Insights In the realm of SCV, leveraging synthetic image recognition powered by artificial data is a game-changer. Unlike traditional models reliant on real-world data, SCV benefits from synthetic data created through virtual reality - artificial images or videos. This not only simplifies the learning process for SCV models but also holds the unique advantage of synthetic data remaining undiminished over time. This contributes to improved accuracy and more reliable insights for inventory visibility, planogram compliance, competitor analysis, promotional campaigns, and quality control. The significance of this approach amplifies when expanding image recognition capabilities across diverse catalogues and retail locations. Recognising that the efficacy of image recognition, whether synthetic or traditional, hinges on the quality of its data, synthetic data emerges as the rising star. Fuelled by the reasons and benefits outlined above, synthetic data is swiftly becoming the preferred choice, outshining its real-world counterpart. Technology When it comes to image recognition, traditional methods face numerous challenges. Among the most common is the vast amounts of real-world data necessary to sufficiently train algorithms. This process is both time-consuming and costly due to the requirements of data collection and annotation. Compounding this, traditional methods often struggle with a lack of data diversity, limiting the range of scenarios the algorithm can effectively learn. This limitation contrasts sharply with the diverse scenarios encountered in the real world. As a result, traditional IR acts as a bottleneck, needlessly hindering the operations of CPGs. Introducing Neurolabs’ ZIA Our cutting-edge synthetic image recognition technology, ZIA standing for Zero Image Annotations, is at the forefront of innovation. Using 3D assets of CPG products and virtual scenes, ZIA delivers product detection and in-shelf insights faster, more accurately, and at a lower cost than any other solution available. The capabilities of ZIA include: Annotation Independence ZIA eliminates the need for laborious manual image annotations, saving time and money while streamlining the recognition process. Cost-Effective Scaling Users can effortlessly scale operations with ZIA, ensuring a cost-effective and efficient pathway to growth. Rapid Onboarding ZIA offers a remarkable onboarding experience, getting users up and running within a mere 24 hours. You can also onboard SKUs in minutes with our ZIA Capture app. Expert Support With a dedicated customer support team, ZIA ensures that any challenges are swiftly addressed and resolved within a quick 24-hour turnaround. Reliable data and insights With ZIA you can achieve a visual detection accuracy rate of +95% from the outset and increase to above 98% for specific categories. You can also access our ChatCPG AI Assistant to extract reliable insights from your data in seconds! Elevating CPG Operations with SCV Synthetic Computer Vision (SCV) emerges as the driving force behind operational excellence for Consumer Packaged Goods (CPG). Let's explore the impactful roles it plays: Product Detection and Classification: SCV brings automation to the forefront by swiftly and accurately detecting and classifying products on store shelves. This helps CPG brands to ensure that their products are properly displayed and stocked according to the relevant planogram compliance standards. Additionally, SCV's prowess extends to tracking inventory levels with precision, ensuring a seamless and compliant supply chain. Precision in Deformed Product Detection: SCV goes above and beyond by showcasing its ability to identify deformed products, a particularly invaluable feature when auditing items with soft packaging like crisps or frozen produce. The accuracy of SCV shines through, contributing to a more precise and reliable product inspection and data collection process. Precision in Stock Level Estimation: Transforming inventory management, SCV empowers CPG brands with accurate stock level estimations, proactively preventing Out-of-Stock (OOS) and dead stock scenarios. This ensures well-informed stocking decisions, mitigating the risks associated with costly stock-related mistakes. Strategic Backroom to Storefront Integration: In the intricate dance of inventory, SCV acts as a linchpin, enhancing the connection between the backroom and storefront through real-time tracking of inventory levels. This dynamic feature ensures a constant flow of stock to the shelves, minimising the likelihood of out-of-stock situations and enhancing overall operational efficiency. Strategic Analysis of POP Displays and Signage: SCV takes centre stage in meticulously analysing Point-of-Purchase (POP) Displays and Signage, ensuring a flawless presentation of products within the store. This meticulous attention to detail becomes a cornerstone for an enhanced customer experience and a direct contributor to revenue growth. Elevating Customer Experience in Competitive Categories: In fiercely competitive sectors like FMCG, Home Appliances, Telecom, and Electronics, SCV becomes a crucial ally, delivering those marginal gains indispensable for effective competition. By ensuring products are accurately displayed, SCV not only improves the overall customer experience but also strategically boosts revenue in these highly contested categories. Efficient Algorithm Training: SCV doesn't just offer speed but efficiency in training algorithms, translating to faster and more cost-effective scaling. This implies substantial growth with reduced investment, making SCV a strategic choice for businesses aiming to expand their operations. Proactive Training Ahead of Shelves: A game-changer in time-sensitive scenarios, SCV can be trained before products hit the shelves, requiring only the artwork. This guarantees swift detection and provides accurate insights, as the technology is pre-equipped with knowledge about the promoted products, ideal for POP campaigns and trade promotions with shorter lead times. Direct Impact on Operational Scale: We've witnessed firsthand the transformative power of SCV in action. By assisting one of our partners, a global beverage CPG, in scaling their operations, we cut down the implementation time from over 6 months with traditional methods to a mere 2 months. Moreover, the results spoke volumes, delivering significant ROI at a fraction of the cost. It's a testament to the real and substantial impact SCV can have on business growth. Elevate Your Retail Shelf Auditing with Synthetic Computer Vision The adoption of synthetic computer vision is now indispensable for achieving effective retail execution. CPGs that fail to adapt risk falling behind in the current competitive landscape and compromising their future success. To ensure you stay ahead of your competitors, book your demo today. At Neurolabs, we are revolutionising in-store retail performance with our advanced image recognition technology, ZIA. Our cutting-edge technology enables retailers, field marketing agencies and CPG brands to optimise store execution, enhance the customer experience, and boost revenue as we build the most comprehensive 3D asset library for product recognition in the CPG industry.

We're thrilled to announce a significant milestone in our journey towards transforming the world of AI and Computer Vision (CV). We have been awarded a prestigious grant from Innovate UK, a leading organisation dedicated to driving innovation, economic growth, and business development in the United Kingdom. But what does this funding mean for us, and why is it such a big deal? Let's dive into the details and explore the exciting future that lies ahead. At Neurolabs, we’re on a mission to democratise CV and our unique approach harnesses the power of synthetic data to simulate complex real-world scenarios, making object recognition faster and more cost-effective than ever before. Importantly, our synthetic data includes pixel-level annotations, eliminating a major obstacle and cost driver in the world of deep learning computer vision models. Building on this innovative technology, we have created a low-code computer vision platform that offers object recognition as a service. This eliminates the need for extensive data acquisition or model training for our enterprise customers, enabling them to onboard 10 times faster than competitors. Our primary focus is on the supply chain of consumer packaged goods (CPG) in retail and beyond. The challenge we are addressing is the development of robust and generalisable object recognition models that can be used across various use cases without the need for extensive model training and data preparation. To tackle this challenge, we are collaborating with a team of experts from the University of Edinburgh who are leaders in diffusion-based optimisation algorithms. This partnership will pave the way for the creation of algorithms tailored to optimise the training of object recognition models for CPG applications. At Neurolabs, we envision a future where our computer vision technology becomes a "plug-and-play" platform, adaptable to various industries and use cases across the CPG supply chain. From product sorting in waste management to autonomous checkout stores and inventory visibility in warehouses, the possibilities are endless. Our collaboration with the University of Edinburgh and the South Korean project team at UNIST will lead to the development of computer vision models with absolute performance guarantees. These foundational models will provide cross-domain generalisability, streamlining model development and minimising the need for specialised models for each use case. We are committed to democratising computer vision, ensuring that small, medium-sized and large enterprises can harness the transformative power of our technology. As part of our dedication to the community, we will open-source some of our groundbreaking algorithms developed, expanding their applicability beyond our proprietary models. The funding from Innovate UK will enable us to: Accelerate the development of robust and generalisable object recognition models. Expand our technology's reach across various use cases within the CPG supply chain. Establish ourselves as leaders in the rapidly growing field of computer vision. Our work also aligns with the UK government's vision to establish the country as an AI powerhouse and reduce dependence on non-UK businesses in this rapidly evolving landscape. In the coming years, we are poised to transform the world of computer vision, making it more accessible, efficient, and adaptable than ever before. We look forward to a future where our technology enhances productivity, drives innovation, and leads the way in the supply chain of consumer packaged goods. If you would like to find out more about our technology and how it can transform your retail operations simply book a demo and speak to one of our experts. Alternatively, if you’re looking for an image recognition partner, take a look at how you can become a partner today. For all press and media enquiries, please contact us at hello@neurolabs.ai At Neurolabs, we are revolutionising in-store retail performance with our advanced image recognition technology, ZIA. Our cutting-edge technology enables retailers, field marketing agencies and CPG brands to optimise store execution, enhance the customer experience, and boost revenue as we build the most comprehensive 3D asset library for product recognition in the CPG industry.

In the ever-evolving world of retail, where competition is endless, innovation is the lifeline for staying one step ahead. Within this dynamic landscape, our synthetic image recognition technology stands as a revolutionary force, redefining the rules of the game. It's not just a step forward; it's a monumental leap, improving accuracy and decreasing time-to-market from weeks or months to mere days. In this blog post, we're thrilled to introduce you to the latest breakthrough stemming from our Synthetic Image Recognition Technology. Meet our AI-powered Retail Execution assistant, ChatCPG, designed to turbocharge your marketing strategy and elevate your promotional materials. Think of it as ChatGPT tailor-made for CPGs – a game-changer that takes data and insight extraction to unparalleled heights. Best of all, it's as straightforward as asking your REX questions and receiving answers in a matter of seconds! Before we delve into the exciting world of ChatCPG and its transformative potential for POP materials, let's start by clarifying some key terms. POP Displays Pop Displays are short for Point of Purchase Displays, are strategically designed structures within retail spaces. They showcase products in an appealing manner, grabbing the attention of shoppers and increasing the likelihood of in-store purchases. POP Signage Pop Signage or Point of Purchase Signage, encompasses a variety of printed materials used in retail settings. These materials provide customers with essential information, aiding their purchase decisions. From product details to promotions, POP Signage guides shoppers effectively. The below images show a floor decal for brand Waterloo, endcap display for KitKat and a promotional in-store banner hung from the ceiling. POP Materials Pop Materials or Point of Purchase Materials, constitute a wide array of marketing collateral deployed in retail environments. These materials support product promotion and sales, enhancing brand visibility. POP Materials include displays, signage, and marketing collateral aimed at engaging and converting customers. The below images show a Nescafe shelf talker, an in-store demonstration for brand noberasco and a freestanding display for Sainsbury's. Globally, we’re still in the early stages of generative AI adoption in the workplace, with retail giants like Walmart leading the charge. We share their belief in the immense potential of AI when deployed effectively. A study from the National Bureau of Economic Research in 2023 revealed that generative AI increased workplace productivity by a remarkable 14%. Nevertheless, some firms remain hesitant or have even banned AI innovation. Let's take a look at ChatCPG Powered by our cutting-edge Synthetic Image Recognition technology, known as ZIA (Zero Image Annotations), our AI Retail Execution assistant, ChatCPG, harnesses the wealth of image recognition data collected during store visits. It takes this data and overlays an intelligent layer, allowing you to pose a wide spectrum of Retail Execution (REX) questions and receive reliable responses - all within seconds! The process is remarkably straightforward. Simply engage with ChatCPG using natural language, asking anything related to your captured data, whether it's queries about shelf compliance, product availability, or adherence to promotional materials (such as POP Displays and POP Signage). However, in this post, our focus will be exclusively on the last category: Promotional Materials. In the below example, we have a photo of an Apple display showcasing the latest iPhones. Each mobile is accompanied by enticing offers that highlight product features, promotions, and other incentives. With the help of ChatCPG, you can effortlessly inquire about any questions related to POP material, whether it's about the number of ongoing promotions or even the fine print in the terms and conditions, and receive an immediate and reliable answer. Elevating POP Displays and Signage with Synthetic Image Recognition When Synthetic Image Recognition joins forces with AI, CPG brands gain a competitive edge and the ability to make informed decisions, driving growth. Synthetic Image Recognition empowers CPGs with comprehensive, real-time data across their entire Retail Execution operation. It eliminates the need for labour-intensive, human-in-the-loop audits of POP displays and signage. Synthetic Image Recognition can identify brands, recognise prices, and even match prices with the correct brand and product size, regardless of granularity. This empowers CPG brands to: Understand the performance of POP Materials on a large scale. Determine which promotions outperform others. Ensure POP materials are displayed and they are compliant across different retail locations. Manage inventory associated with POP campaigns effectively. Gain insights into materials that capture attention and drive conversions. Make data-driven decisions guiding design, placement, and distribution for optimised retail execution. Overall, synthetic image recognition equips CPG brands with a powerful tool for deploying and managing POP Materials. By harnessing this technology, CPG brands can enhance retail execution, boost sales, and secure a competitive edge in the market. How ChatCPG Addresses POP Material Challenges No More Spreadsheets! It’s likely that without an assistant like ChatCPG you’d need to have a database in some sort of format. This can be an in-house solution or an external provider, or a complex, inflexible spreadsheet in which you’ll find it difficult to pull out useful insights. The latter option can become complicated quickly as you add more information. Which means, eventually your spreadsheet will be like having a family car but needed to go racing, your needs have changed, but your tools haven’t, therefore you’re left behind. Another aspect to consider is the quality, or lack thereof, of the data you can access with non AI solutions. Utilising AI means you’ll have a richer pool of data to gain insights and make more informed decisions from. A Data Analyst Who Is Always Available It’s common for spreadsheets to require more people to manage them as they grow in size and complexity. You’re also leaving yourself vulnerable to missing out on opportunities if the designated person/people isn’t/aren’t available through an absence. ChatCPG eliminates these problems as it becomes your ‘always available data analyst’ automating the data gathering stage, enabling you to focus on interpreting your insights. Leverage real-time insights React swiftly to shifting market conditions with real-time insights into POP Material performance, obtained by simply querying an AI. Consider this hypothetical scenario: You encounter compliance issues with POP Signage in a particular store. Instead of relying on human interpretation or complex spreadsheets, you ask ChatCPG, receiving an accurate response in seconds. Don’t miss out on scaling opportunities If the resources required to manage and improve your POP Materials increases exponentially along with the amount of POP Materials you have - then you can’t scale. However, having a resource like ChatCPG can reduce the resource demand significantly. This means you not only have the information needed to scale, but you’re also regaining vital resources - staff, finances, time, technology to invest into scaling effectively. Unlock the Full Potential of Your POP Materials Ready to revolutionise your retail strategy? Synthetic Image Recognition and ChatCPG is your all-in-one AI solution for optimising POP Materials and more. Discover how ChatCPG, powered by Synthetic Image Recognition technology, can empower your brand. Book a demo today! At Neurolabs, we are revolutionising in-store retail performance with our advanced image recognition technology, ZIA. Our cutting-edge technology enables retailers, field marketing agencies and CPG brands to optimise store execution, enhance the customer experience, and boost revenue as we build the most comprehensive 3D asset library for product recognition in the CPG industry.

Point of Purchase (POP) materials are the unsung heroes of retail, comprising promotional displays, signage, and advertising materials strategically placed within stores. They play a pivotal role in the success of retail strategies, acting as the silent influencers that guide consumer decisions and drive sales. Yet, in today's competitive marketplace, many businesses are unwittingly leaving untapped revenue potential on the store shelves. In this article, we delve into the world of POP materials and how the integration of synthetic image recognition can revolutionise their effectiveness. There are an array of Promotional Materials that are used in retail, these include posters, banners, displays, shelf talkers, end cap displays, sampling stations, floor graphics, window decals and more. Below are some examples: The Current State of POP Materials The challenges with POP materials are two-fold: Poor visibility on POP campaigns Field agents working on POP campaigns often find themselves trapped in a laborious, manual compliance verifying process. This involves filling out binary (Yes/No) questionnaires and physically inspecting stores to confirm the presence or absence of a POP display. After this, another agent must do a Quality Control check to verify the work of this first agent. This inefficiency is compounded by the fact that a simple "yes" or "no" answer doesn't provide sufficient insight into the condition and performance of the POP campaign. This brings us to the second major issue. Poor ROI due to limited insights When consumer packaged goods (CPG) companies invest significant resources into POP campaigns, receiving only binary feedback – the display was or wasn't there – is far from satisfactory. This incomplete data leaves them in the dark about what is happening in the store. Vital questions remain unanswered: Is the shelf stocked appropriately? Are the displays in the right condition? Are the POP materials positioned correctly next to the relevant SKUs? This lack of detailed insights hinders CPGs from making informed decisions about their next steps. For example: Which POP materials are driving the most sales, and why? Is the POP campaign effective? Is the POP display effective? Should they consider changing the placement of their products near POP displays? If they don’t then essentially their POP campaigns will become increasingly inadequate. To the point where it becomes a major weakness, preventing them from keeping up with, let alone outperforming their competitors. The Role of Synthetic Image Recognition (SIR) SIR’s main role is to extract insights and provide a high level of visibility into POP campaigns. In addition to this, it has three other important functions. Actionable insights SIR provides insights that don’t require human validation in the form of Quality Control. The insights are produced through the validation of product and shelf images. Ease of Use Implementing SIR is a straightforward process. For POP materials, all that's required is a PDF or reference image. Alternatively, ZIA Capture, our onboarding app, can be utilised if new POP displays are detected without available PDFs or images. Once the initial setup is complete (this usually takes a day), the system runs autonomously. No human intervention is necessary. Scalability Our technology is designed to accommodate large-scale operations. Some of our clients onboard and audit more than 700 POP displays every month. About half of these change on a monthly basis. The total number of images runs into the millions each month. ChatCPG makes managing POP materials easy Investing in data and insight acquisition is great, but how do you go about accurately understanding the data? Do you use a dashboard? Maybe you’re spread thinly across static spreadsheets. A combination of both? All of these options are holding you back from getting the insights you need. Meet ChatCPG, your AI Retail Execution assistant, or your AI Data Science Assistant. When your image recognition data is collected with our synthetic IR technology, ZIA (Zero Image Annotations), ChatCPG reads and interprets this data so you can ask it any REX question. Think of it as Alexa, Siri or Google Assistant, but specifically for your retail execution operations. You can ask it questions in natural language such as: "Do the POP displays for Nestle products in London Tesco stores have the correct pricing?" "Is there any damage to our POP materials in any Albert Heijn stores in the Netherlands?" "What are the SKUs next to our POP displays in Oxford Street Selfridges?" And receive accurate responses in seconds, eliminating the need for complex dashboards or raw data analysis. Plus, it minimises the need for additional human involvement, providing instant insights into your retail execution, making it as simple as ordering an Uber. Ensure that your POP materials not only grab attention but also lead to purchases The integration of synthetic image recognition technology holds the key to unlocking the full potential of your POP materials. By streamlining the auditing process and providing detailed insights, businesses can make data-driven decisions that enhance the effectiveness of their retail execution strategies, ultimately boosting their competitive edge in the market. Don't miss out on the opportunity to revolutionise your POP campaigns; embrace the power of synthetic image recognition today and schedule your free demo. At Neurolabs, we are revolutionising in-store retail performance with our advanced image recognition technology, ZIA. Our cutting-edge technology enables retailers, field marketing agencies and CPG brands to optimise store execution, enhance the customer experience, and boost revenue as we build the most comprehensive 3D asset library for product recognition in the CPG industry.

It’s often said that the world of business is cut-throat, and with an approximate estimate of over 333 million companies worldwide, it’s easy to see why this viewpoint has prevailed over the years. With a value of $5.3 trillion in annual sales, the CPG (Consumer Packaged Goods) sector is an immensely competitive space. Regardless of the product your company specialises in, there is always significant competition as existing companies venture into new markets and new brands appear on the market to challenge the status quo. However, due to numerous economic and geopolitical factors, more than half of all CPG companies are on track to grow below the market (rate) by 2027. The data from Kearney shows that inefficient supply chains will cost CPGs a potential $800 billion. However, it’s clear to see that this deficit will only intensify the competition in the CPG space and force all but the top brands to compete for a lesser pool of revenue. While there is a significant amount of risk involved, the biggest brands all scale their businesses to reach as many consumers as possible. However, for scalability to genuinely work for all CPGs (including those that are more risk-averse), there needs to be an affordable solution that helps CPGs resolve many of the issues associated with global scalability. Thankfully, one affordable solution you’ve been searching for is already here. In this article, we will explore how Neurolabs' ZIA offers groundbreaking image recognition tech that easily integrates with existing platforms to help CPGs resolve several issues, such as retail store execution and inventory management. Read on to find out how our AI-powered solution delivers scalability and efficiency to help CPGs of all sizes compete in a crowded and fast-growing industry. What is ZIA? ZIA stands for Zero Image Annotations and is our groundbreaking technology revolutionising in-store image recognition for CPGs. Eliminating the need for manual annotations and even real data itself, ZIA uses 3D assets of CPG products (synthetic data) in virtual scenes (synthetic computer vision) to deliver product detection and in-shelf insights more accurately and faster than any other solution that is currently available. Neurolabs’ ZIA technology can simulate SKUs in multiple retail scenarios from just packaging labels resulting in a product detection rate of 95% from day one (and 98%+ for specific SKU categories). What are the benefits of ZIA for CPGs? Neurolabs’ ZIA delivers numerous benefits for CPGs regardless of their size or industry focus. Thanks to the power of synthetic data and the synthetic computer vision that drives ZIA, we deliver a wealth of perks and benefits to help CPGs, providing them with an easily integrable, cost-effective and scalable image recognition solution. Global scalability ZIA can deliver accurate and consistent performance to CPG brands of all sizes, even those with a considerably extensive catalogue that extends to multiple markets and territories. Neurolabs’ ZIA offers an efficient and cost-effective way to scale operations globally by streamlining product catalogues across multiple retail regions and locations with ease. With ZIA, there is no lengthy onboarding process either, as our solution is ready to be used across your entire product line in as little as one week. Besides being fast-to-market, ZIA is a robust technology that works accurately across thousands of store locations. At Neurolabs, we make use of the same standardised process to set up the technology and ensure it is capable of detecting your products in every territory. By accessing your master product catalogue ZIA not only saves you time (e.g. taking lots of real store images or providing reference product images) but also provides you with a platform that allows you to enter new markets without image recognition concerns. In addition, ZIA also allows users to tweak their inventory over time, making it incredibly effective at providing IR for their new products/any promotions as and when they launch. ZIA can achieve all of this and more without compromising performance when scaling your catalogue. Cost efficiency Synthetic data generation is a far more cost-effective way to gather data for image recognition learning models than real data, as it requires minimal human input to collect and verify data sets. As the name of our software implies, ZIA requires Zero Image Annotations as its synthetically trained model allows it to automatically detect individual products. Therefore, our image solution is not only cost-efficient but saves considerable time and effort, allowing CPGs to get IR on their latest products and hit the ground running when onboarding our technology. Ease of integration At Neurolabs, we are aware that many CPGs may already have invested in image recognition technologies to enhance their operations and, as such, aren’t looking for an all-in-one solution. However, with ZIA, we offer a service that effortlessly integrates with existing SFA tools (including third-party SFA or internal tools) and enhances their processes with the power of synthetic data. ZIA is able to work with an existing SFA solution (or even a different SFA solution per region or location). It is intuitive enough that your staff do not require additional training to learn the ropes of how the platform works. However, should you need any assistance to help get ZIA implemented in your pipeline, we have a team of dedicated and knowledgeable experts on hand to answer any questions or concerns you may have. Boost your revenue with Neurolabs’ ZIA ZIA is a genuine game-changer allowing your brand to improve your processes and dramatically boost your revenue. Accurate, reliable, cost-effective and easily integrated with existing technologies, ZIA is the next-generation tech that will fundamentally change your perception of image recognition. With ZIA, you can achieve better detection accuracy, a faster time-to-market, lower set up and maintenance costs while easily being able to streamline product catalogues across multiple retail locations and countries. Say goodbye to your existing inaccurate and inefficient platform today and embark on a journey of discovery with the image recognition solution of the future. Interested in learning more? Then click here to Request a Demo! At Neurolabs, we are revolutionising in-store retail performance with our advanced image recognition technology, ZIA. Our cutting-edge technology enables retailers, field marketing agencies and CPG brands to optimise store execution, enhance the customer experience, and boost revenue as we build the most comprehensive 3D asset library for product recognition in the CPG industry.

A lot less than you think. We’re not just talking about money directly, there are many ways that Synthetic Image Recognition (IR) can bring down the cost of your operations. We’ll explain what they are in this blog post. The cost of Traditional Image Recognition technology Before we dive into the costs of synthetic image recognition, we need to establish the holistic costs of its inferior predecessor, traditional image recognition. It costs too much time One example of how time intensive traditional IR is that there is a dominant IR supplier based in Asia. This supplier employs thousands of staff to manually annotate images and validate predictions. If you were to use this method you’ll be repeatedly held back from scaling your operations, simply because the process takes too long. With traditional image recognition the time it’d take to scale would become exponentially longer. It costs too much in staff As you saw in the previous example, it takes a lot of people to operate traditional image recognition technology, and all those people need to be paid. Manual annotation is a laborious , repetitive task, which pretty much every human, at minimum, doesn't enjoy. This results in a human-error rate of >5% in a human curated/annotated dataset. Traditional IR is wholly dependent on this fragile process. The cost is also passed onto the end customer. Having a human in the loop is a drain on both finances and time. Poor data accuracy is expensive As there is so much human intervention, the higher the number of SKUs to process, the higher the likelihood that your catalogue will have errors in it. This problem is exacerbated when annotating products that have little visual differences, bar a few minor packaging adjustments. When building and managing a catalogue, data accuracy is everything. If you can’t rely on your data, you can’t operate with confidence, double checking and triple checking takes time and creates anxiety. Scaling effectively is nigh on impossible If you’re held back by spiralling financial costs, time costs, staff costs and data inaccuracies, how do you scale? Well, you can’t. Using traditional IR methods, by the time you scale to your desired goals, your competitors will have left you behind. The entire industry will have shifted and your new level of operations will be irrelevant. On top of all these issues, to get to this level you would’ve spent a small fortune in time, staff and money - so there isn’t any ROI. This makes it impossible to remain competitive in the long term and can lead to total business failure. The factors affecting the cost of traditional Image Recognition Technology Data Collection - The efficacy of how the data is collected is crucial to making a business case for IR. If data can’t be collected quickly and cost effectively your Shelf Auditing process will fail as you scale. On the flip side, efficient data collection can transform your process, by enabling you to scale your operations at your desired speed with no significant increase in effort. Data hygiene - Having to manually annotate your data reduces the likelihood you’ll be able to trust it. The quality of the data is vital to the level of performance you can achieve. If you can’t trust your data, there isn’t much point in collecting it in the first place. Model training - Your model is only as good as its training. Being able to use synthetic data to do so enhances this process. Model deployment - This involves keeping the model live, think of the hardware that makes the software work. Model maintenance - This consists of numbers 1-3. Additionally it includes model deployment, which ensures that the model deployed is live all the time, or at the desired time. How traditional IR technology affects Retail Execution Planogram Compliance These will have to be manually checked by staff in order to achieve compliance. This can lead to the effectiveness of the displays declining as items aren’t arranged properly. Manual processes lack reliable accuracy, especially at scale, which contributes to the data quality issue we mentioned earlier in the blog post. Stock Levels The low level of accuracy when annotating high numbers of SKUs means that stock data is likely to become inaccurate, which negatively affects the ability to respond to any changes in consumer demands. Pricing and Promotions Similar to stock levels, if the data hygiene is poor the chances of price discrepancies is higher. In addition to customers being misled, pricing agreements between Consumer Packaged Goods brands ( CPGs) and retailers can end up being broken. Issues like this can cause contracts to be voided or terminated. Product Placement Having to carry this out manually can lead to mistakes and a decrease in KPIs for CPGs, which puts pressure back on Field Marketing Agencies (FMAs). Point of Sale Materials Similar to product placement, traditional IR means that the accuracy of these materials is at risk. This will also have a knock on negative effect on KPIs. Competitor Analysis As traditional IR has an increasingly low level of accuracy as you ramp up operations, it’s unlikely that you can rely on the data to perform any type of valuable competitor analysis. How Synthetic Image Recognition technology affects Retail Execution Planogram Compliance Using the target planogram synthetic image recognition can quickly and accurately compare it against store layouts, identifying any discrepancies. This ensures that planograms are adhered to and can be accurately reported on. Stock Levels You can accurately detect when a particular product is out of stock, or is about to be. This makes it easier to respond to changes in consumer demands. Product Placement Products will now be placed where they should be, as Synthetic IR can recognise products and labels, even in disorganised environments. Point of Sale Materials Following on from product placement, the technology can accurately identify and locate POS materials. This helps to confirm that promotional materials are correctly positioned and visually appealing. Competitor Analysis By analysing shelf images from different stores or locations, synthetic image recognition can detect and compare products from different brands. This allows retailers and brands to conduct competitor analysis, understand shelf positioning, and identify market trends. Quality Checks Synthetic IR also helps to ensure that the right quality of product is available, not just the right product. It can recognise damaged and expired items which can be replaced with untouched and fresh products. The cost of Synthetic Image Recognition The Technology This is the main thing you’ll have to pay for/with. Once you have this, it’s all systems go, because as you’ll read in the next section, and probably already know by now, Synthetic IR is far superior to its older sibling. Synthetic Image Recognition vs Traditional Image Recognition Cost Unlike traditional IR the cost of Synthetic IR doesn’t increase exponentially as you increase the amount of SKUs. However, this is the case with traditional IR, the more SKUs you add, the more expensive it becomes. This means you can quickly scale your catalogue without committing an exponentially large amount of investment. This is largely down to synthetic IR not needing the process to increase in complexity of elements such as data curation, human in the loop, training etc. Accuracy Unlike traditional IR, data accuracy levels don’t exponentially deteriorate as you scale. This means you can trust your data more as you grow your operations vs. traditional IR. Speed Synthetic Image Recognition is significantly faster than the traditional version. It’ll take weeks as you expand your catalogue with the old technology, whereas, even with over 1000 SKUs it still won’t take more than a day doing things the synthetic way. Remember the image below anytime you doubt/or have to convince anyone of the benefits of synthetic over traditional image recognition. We've explained how synthetic IR can make your working life, more lucrative, and efficient. Still don't believe us? Try our free demo by clicking the link below. At Neurolabs, we are revolutionising in-store retail performance with our advanced image recognition technology, ZIA. Our cutting-edge technology enables retailers, field marketing agencies and CPG brands to optimise store execution, enhance the customer experience, and boost revenue as we build the most comprehensive 3D asset library for product recognition in the CPG industry.

The Consumer Packaged Goods (CPG) industry is often hindered by a significant disconnect between Trade Promotion (TPx) and Retail Execution (REX) when implementing in-store promotions. Research conducted by POI found that 75% of CPG brands struggle to execute their in-store promotions effectively. This may be due to several factors, including poor strategy, limited resources, ineffective communication, or inadequate measurement and evaluation capabilities. These challenges hinder CPG brands from achieving healthy ROI in one of their key marketing channels, rendering the resources poured into these activities ineffective. Therefore, addressing the issues associated with implementing in-store marketing campaigns is vital. The CPG industry cannot afford to continue like this, as there are significant implications in terms of lost revenue, strained relationships, and diminished brand reputations. This article will show you how to close the gap between REX and TPx with the right technology. The current retail execution landscape Successful retail execution requires effective planning, communication, and evaluation. If these elements are not present, in-store promotions will fail to succeed. Companies may struggle with retail execution for many reasons, including: Poor planning: If the promotional campaign isn't well thought out or intentionally planned, it can hamper the success of in-store promotions. Companies need detailed plans that outline specific responsibilities, tasks, resources, etc. Lack of training: If the promotional campaign isn't compliant, then the training of the employees to implement it will also be negatively affected. Employees that don't have proper training on SKU features (or the details of a specific promotion), won't be engaged or motivated to promote it in-store. Poor communication: The data disconnect spreads out to communication, as the data from the store isn't always relayed back to head office (HQ). For example, HQ creates strategies and communicates them to the staff; however, data from those at the store might not be passed on to HQ. Think of it as a terrible case of the game of 'Pass it On' where the message goes through so many intermediaries that it gets distorted. Lack of real-time data analysis: CPG brands will struggle to adapt because consumer habits can change fast. Without access to data, brands are unable to measure their progress, evaluate trends or strategise for the future. How in-store execution affects the wider industry Ineffective retail execution (REX) can cause several challenges for CPGs, including: A loss of market share/customer churn: As the in-store promotions become less effective, customers are more likely to be put off and flock to competitors. For instance, a 2023 survey of UK consumers found that only 34.2% will remain loyal to a CPG brand if cheaper alternatives are available. Devalued brands: When product displays are disorganised or there are out-of-stock items, this can create a negative perception of the brand, making it even more challenging to compete. More difficult negotiations with retailers: A low or negative marketing ROI can lead to Volume Incentive or Slotting Fee deals becoming harder to agree on, as the CPG brand has less leverage in negotiations. Failed new products: When in-store execution fails, it can hamper the success of new product launches. If stores aren't prepared to handle new products, it results in a lack of brand awareness, poor product placement, or inadequate shelf space. Ultimately, when in-store execution fails, it causes a ripple effect throughout the industry - impacting sales, brand reputation, retailer relationships, etc. However, synthetic image recognition technology is emerging to address these problems and create new business growth opportunities. How synthetic IR is helping CPG brands improve their in-store execution Synthetic image recognition uses synthetic computer vision to create 3D digital replicas of SKUs and retail displays. Find out more about how it works in this previous article. There are many reasons why this revolutionary technology is making waves in the CPG space, including: Trade Promotion Optimisation TPx optimisation is a critical aspect of CPG marketing strategies. Synthetic IR can analyse in-store images to evaluate the effectiveness of promotions; it's even able to detect fine-grain detail and work in environments with complex lighting and challenging conditions. Brands can then determine if the promotions are executed correctly in terms of product placement, signage, pricing, and promotional materials. This helps CPGs identify discrepancies and ensure that trade promotions are properly implemented – maximising their impact and return on investment. Compliance Monitoring Synthetic IR technology can monitor compliance with trade promotion guidelines and policies by analysing images to detect and assess in-store compliance metrics. For example, it can identify the proper display of promotional materials, adherence to pricing guidelines, and inclusion of all designated products. Brands can use this information to identify non-compliant stores, take corrective actions, and enforce compliance. These crucial checks ensure that promotions are executed consistently across different retail locations. Shelf Share Analysis Synthetic IR can accurately assess the shelf share of a brand's products in-store. It can analyse shelf images and determine the percentage of shelf space occupied by a specific brand compared to its competitors. This information helps CPG brands evaluate their market presence, track shelf share changes over time, and assess the overall effectiveness of their retail execution strategies. By understanding their shelf share, brands can make informed decisions to improve their product visibility and market positioning. Real-Time Data and Analytics Synthetic image recognition provides real-time data and analytics on TPx and REX. Analysing in-store images and extracting valuable insights helps brands access accurate and up-to-date information about the execution of their trade promotions, product placements, pricing, and other relevant factors. Real-time data allows brands to make informed decisions, respond quickly to execution issues, and adjust strategies promptly, maximising the impact of their TPx and REX efforts. Introducing Neurolabs ChatCPG Neurolabs' AI-driven shelf auditing assistant, ChatCPG, is making capturing data and gleaning insights from synthetic IR technology simpler than ever. You don't need any extra dashboards, data sets or deep investigation - simply converse in natural language with ChatCPG to receive instant, accurate answers. This remarkable CPG sector breakthrough enables access to actionable intelligence more quickly and efficiently than ever before. You can find out more about ChatCPG here. How Synthetic IR improves Competitive Analysis Synthetic IR enables CPG brands to analyse in-store images to gain insights into their competitors' TPx and REX activities. Brands can compare promotional displays, pricing strategies, product placements, and more. This information helps identify areas of competitive advantage or areas for improvement. From here, brands can refine their own TPx and REX approaches to stay ahead in the market. Moreover, synthetic IR's speed, accuracy, scalability, and cost efficiency are particularly noteworthy. For example, with Neurolabs ZIA, CPGs or field reps can add new SKU imagery via the ZIA Capture app and generate synthetic data to train its object detection algorithm within a few minutes – four times faster to market than traditional IR solutions. This means a field rep can complete an in-store auditing visit eight times faster than traditional IR technology. Additionally, because ZIA utilises a synthetic dataset and does not rely on real data, it provides more diverse training data, leading to better accuracy that does not degrade over time. Don't miss out: Try Neurolabs ZIA today Synthetic IR is gaining traction in retail, with many global players adopting this new generation IR to take their TPx and REX strategies to the next level. Brands that harness the power of synthetic image recognition solutions offered by Neurolabs ZIA (with new features like ChatCPG) are better equipped to improve their in-store execution. Our solution easily detects out-of-stocks, empowers CPGs to organise their shelves efficiently and ensures price and promotion accuracy. It can also help you leverage information from data insights to help improve KPIs. For instance, it can foster faster implementation and promote high precision, scalability, and cost-effectiveness, all while creating new growth opportunities. Get in touch for more information on how Synthetic IR can benefit your business. At Neurolabs, we are revolutionising in-store retail performance with our advanced image recognition technology, ZIA. Our cutting-edge technology enables retailers, field marketing agencies and CPG brands to optimise store execution, enhance the customer experience, and boost revenue as we build the most comprehensive 3D asset library for product recognition in the CPG industry.

Onboarding SKUs to your catalogue shouldn’t feel like you’re training to be in the Navy Seals. It should be similar to calling an Uber: A few taps, a short wait, and voila, the process is complete. Take a look at the process in this blog post to see how it works, and how you can benefit from it. Our app, ZIA Capture, makes this possible. Why did we build ZIA Capture? For a long time, onboarding SKUs was a clunky, time consuming, and expensive process. We realised that you shouldn’t be the ones to provide photogrammetry references as this can sometimes be difficult. You often have to recruit a 3rd party to do this, and it won’t come cheap. We believe that you shouldn’t have to use an IR vendor that takes weeks to collect enough training data. This has a negative knock on effect which prevents you from reacting quickly and effectively to market conditions. We believe that you should be able to have easy access to high quality 3D assets, with minimal/no human in the loop processes. We also wanted to make the process as easy as possible, all you need is an iPhone! We believed we could create a solution that makes the day to day working lives of Field Marketing Agents easier, more efficient and more lucrative. And we were right. You can see how, below. How does ZIA Capture work? We’ve broken the process down below into 5 simple steps. Step 1 - Download ZIA Capture from the App store onto your iPhone. Step 2 - Open the app, enter the product name and choose either “Box” for boxes or anything rectangular shaped or ‘Freeform’ for anything that isn’t a box. For this first example, we will select the 'Box' option. Step 3 - For the best results, place the item you want to onboard on a flat surface. Our app will guide you through the process of photographing your product with easy to follow instructions. Step 4 - When all sides have been captured, hit “Submit”. Step 5 - The product is now added to your catalogue. Head on over to your catalogue to view in detail. Process for freeform SKUs: Step 1 - Download ZIA Capture from the App store onto your iPhone. Step 2 - Open the app, enter the product name and select the “Freeform” option under “Type”. Hit “Start”. Step 3 - The app will show you how to move around the product so it can capture the images it needs to build the 3D model for your catalogue. Simply follow the instructions and when complete hit the ‘Submit’ button. Step 4 - The images will then be uploaded into your catalogue and a 3D model of the product will be created in a matter of hours. Head on over to your catalogue to view in detail. How does it make adding SKUs easier? You no longer need product artwork No need to stress about not having the right artwork, you can create an accurate 3D model in minutes and get it onboarded in hours. Automated Barcode Recognition ZIA Capture simplifies the process of adding SKUs to your catalogue by automatically recognising and uploading barcodes. This eliminates the need for manual input of EAN/UPC codes, making it effortless for you to search and report on your products and categories within your catalogue. Onboard products in hours not weeks And this will only get faster over time as we constantly improve our technology. More resources for you to invest into other tasks ZIA Capture frees up your time and money to invest into other higher ROI areas of your business. More effective Category Management You can now have complete trust in your catalogue data, whilst doing less work, in less time. ZIA Capture and ChatCPG We’ve also created ChatCPG, think of it as your own ChatGPT, but for your retail execution. ZIA Capture helps to customise ChatCPG for your specific needs. To see/read more about it, simply click the banner below. Enhance your Category Management with Synthetic Image Recognition Our technology makes your job easier and more cost effective. To find out more about ZIA Capture, click here to schedule a demo with us. You can also find out more about our other products here. At Neurolabs, we are revolutionising in-store retail performance with our advanced image recognition technology, ZIA. Our cutting-edge technology enables retailers, field marketing agencies and CPG brands to optimise store execution, enhance the customer experience, and boost revenue as we build the most comprehensive 3D asset library for product recognition in the CPG industry.