Eebz launches AI models with GBP £10 million boost

Eebz has launched a new suite of proprietary foundation models for eCommerce data extraction and intelligence, backed by a £10 million investment in AI infrastructure.

The Windsor-based digital shelf analytics provider said the models are designed to address persistent problems in online retail data, including inaccurate information, high operating costs and delays in producing insights. The system continuously analyses publicly available eCommerce signals to create a real-time view of products at SKU level.

At the centre of the launch is what Eebz describes as a self-correcting data engine that can detect and adapt to changes on retailer websites. The approach is intended to reduce the effort needed to maintain large-scale scraping systems and limit disruption to data collection when websites change their structure.

Digital shelf analytics has become increasingly important as more consumer purchases move online and brands seek faster information on pricing, availability, product launches and retail execution. Eebz argued that current methods often rely on fragmented web scraping or delayed third-party datasets, leaving brands with an incomplete or outdated view of their online position.

The company cited Gartner data estimating that poor data quality costs companies across industries an average of USD $12.9 million a year. Its models are designed to reduce false gaps in availability data by identifying only issues with direct commercial significance.

The technology also aims to provide a continuously updated view of category performance and retailer sell-through, allowing users to measure market share and sales in real time rather than relying on panel data that arrives later. Another claimed use is earlier detection of competitor activity, including new product launches and changes in ranging strategy.

Model design

James Sicilia, Head of Data Engineering, outlined how the system has been built. “The system is powered by 12 interconnected foundation models that work together to deliver visibility across the full product lifecycle. From launch through to delisting, the technology can analyse how products are positioned and sold across retailers.

“Eebz customers can now track products with complete accuracy, automatically matching listings to exact SKUs and monitoring them the moment they go live. This enables teams to focus on the products that drive performance. By using lifecycle intelligence, they can cut through noise and prioritise commercial action.

“Customers can also gain a clearer understanding of retailer strategy at a granular level, including how different retailers structure and manage their ranges, and which products they are likely to stock,” said Sicilia.

Eebz was founded by Peter Laughton to address what the company sees as structural weaknesses in digital shelf analytics. It focuses on consumer electronics and technology brands, where product ranges change quickly and online retail performance can shift across multiple markets and sellers.

According to Eebz, its platform monitors more than 1,500 retailers across 80 countries. Customers include Sony, Samsung, Logitech, Turtle Beach and Warner Bros Games.

Data quality

The launch comes as retailers, brands and analytics providers invest more heavily in AI tools to clean, match and interpret large volumes of commercial data. In eCommerce, these challenges often include duplicate product listings, inconsistent naming conventions, sudden website changes and gaps in stock visibility.

Eebz said its models are intended to improve product matching so customers can track exact SKUs from the moment listings go live until they are delisted. That should help teams focus on products with the greatest impact on sales performance rather than spending time on noise in large datasets.

Peter Laughton, Founder, Eebz, said the wider commercial problem is often underestimated. “Bad data in eCommerce is quietly eroding profitability. Over time, it leads to inaccurate forecasting, operational inefficiencies and a breakdown in customer trust, ultimately constraining growth, weakening competitive advantage and, most critically, reducing profitability.

“With this launch, Eebz positions itself at the forefront of a shift. We are moving from reactive analytics to predictive, intelligence-led decision-making in eCommerce. By combining automation, machine learning and our team’s deep understanding of retail dynamics, we can give brands the tools they need. This helps them compete more effectively in an increasingly complex and fast-moving digital landscape.

“We are redefining digital shelf analytics by eliminating inefficiencies and providing immediate access to commercial insight that can transform eCommerce strategies,” said Laughton.