EvaluateLocate Unveils Geospatial AI Model to Predict UK Economic Trends Three Years Ahead

EvaluateLocate has launched Geospatial Predictor 2, a proprietary AI model providing economic and demographic "nowcasts" across the UK at a one-kilometre resolution. For fintech professionals in lending, real estate, and insurance, this capability offers a three-year lead on official government statistics, enabling more precise risk assessment and localized market analysis before traditional data catches up.

What was announced

The launch of Geospatial Predictor 2 marks a significant upgrade to EvaluateLocate’s digital twin platform, introducing a proprietary model capable of forecasting economic trends up to three years ahead of official government statistics. This platform functions as a continuously evolving country-scale digital twin of the United Kingdom, providing immediate insights into a wide array of social, demographic, and economic indicators. By operating at a one-kilometre resolution, the model allows for a level of precision that bypasses the limitations of traditional tabular data storage and rigid geographic reporting zones.

The updated user application provides access to a comprehensive suite of more than 130 metrics. These include detailed measures of economic output, specifically Gross Value Added (GVA), which serves as a primary indicator of the health of local economies. The model also tracks the vitality of various business sectors, allowing users to identify which industries are driving growth in specific areas. Beyond pure economic output, the tool monitors social and human capital factors such as education levels and workforce skills.

For financial services and real estate professionals, the inclusion of earnings data, disposable income levels, and residential property values—including both sales and rents—provides a granular view of local affordability and market heat. In addition to the one-kilometre grid system, the model has been expanded to cover official administrative geographies, including electoral wards, parliamentary constituencies, and the UK Government’s designated Built-Up Areas, ensuring the data can be integrated into existing regulatory and political frameworks.

"By predicting the future trajectory of localised economies, our technology is part of a growing shift towards physical world models on all scales, and complements the proliferation of language-based AI."

Adam Kirby, CEO at EvaluateLocate.

The companies involved

EvaluateLocate is a specialist firm operating in the geospatial artificial intelligence sector. The company’s core focus is the development of proprietary architecture designed to model the physical world at scale. By positioning itself at the forefront of the "digital twin" movement, EvaluateLocate aims to provide a more dynamic alternative to static datasets. The firm’s technology is built to move geospatial analysis away from the traditional confines of official geographic boundaries, which often mask hyper-local economic variations.

Under the leadership of CEO Adam Kirby, the company has focused on creating models that complement the current industry-wide proliferation of language-based AI. While much of the recent focus in the broader technology sector has been on generative text, EvaluateLocate’s work represents the "physical world model" branch of AI development. This involves the synthesis of massive amounts of spatial data to predict human and economic activity. The firm’s proprietary Geospatial Predictor architecture is designed to be scalable, with the potential for application across different national geographies. As an independent specialist in the UK market, the company provides the underlying data infrastructure that allows financial institutions and policy makers to visualize and predict economic trajectories with a degree of spatial resolution that was previously unavailable through public sector data sources.

What this means

The reliance on "lagging indicators" has long been a fundamental weakness in macroeconomic analysis and local credit risk assessment. When official statistics are published months or even years after the fact, they often describe a market reality that has already shifted. This announcement highlights a growing industry demand for "nowcasting"—using alternative data and AI to fill the gap between government reports. As the UK faces volatile economic conditions, the pressure is on traditional data vendors to match this level of granularity. The shift toward one-kilometre resolution modeling suggests that broad regional averages are becoming obsolete for sophisticated fintech applications, particularly in mortgage underwriting and localized commercial lending.