Feasibly, a VC-backed climate AI startup founded by Beth Holloway and Leo Thomson, has been selected by David Skaith, Mayor of York and North Yorkshire Combined Authority (YNYCA) to receive £112,831 to build a geospatial AI platform that supports regional renewable energy planning.

YNYCA is driving one of England’s most ambitious regional decarbonisation programmes, with a commitment to becoming England’s first Carbon Negative region by 2040, backed by a multi-million pound investment programme. Delivering on that ambition requires an unprecedented acceleration in local renewable energy deployment – and that begins with knowing where to build.

Even after the most significant overhaul of the UK’s grid connections process in decades, the reformed grid queue still contains over 380GW of generation and storage projects competing for connection – nearly double the clean capacity the country needs by 2030.

The queue isn’t simply too large; it reflects a deeper problem: identifying which sites, at which scale, on which network infrastructure, can realistically connect within a viable timeframe. This requires manually cross-referencing DNO constraint maps, planning designation layers, land registry records, agricultural classification, and flood risk data. It is a process that takes weeks per site and demands specialist knowledge, meaning thousands of genuinely viable local energy projects never get assessed at all.

Feasibly’s platform changes that. Rather than retrieving and displaying data for a human to interpret, it deploys an AI agent that runs deep geospatial analysis autonomously – querying live network datasets, cross-referencing planning and land classification layers, and reasoning across the full picture of what makes a site viable. It is agentic AI applied to the physical world: given a location, the agent works through the same analytical process an expert would, returning a structured site assessment in seconds that explains not just whether a project is worth pursuing, but precisely why.