Consistent data across a licence area.
Networks increasingly need to know things about the places they serve, not just about their own assets: which buildings lose heat, where demand will change, what condition the ground and the street are in, and how any of that varies across a licence area.
Most of that is currently assembled from local sources of varying quality. A uniformly derived layer removes that variance — which is a different and better argument than “we have more data.”
Where we fit
Building fabric and heat demand context — measured, rather than inferred from registers and meter data alone.
Local authority engagement — networks are increasingly expected to work with the authorities in their area, and the two sides need a shared picture to work from.
Asset and third-party risk context — street-level condition as an input to risk models that currently rely on proxies.
Innovation programmes — we’re built to be a well-scoped work package inside a larger project, not to be the whole project.
How we work with networks
We are comfortable being a supplier of a layer rather than the owner of a platform. If a programme already has a platform, we feed it. If it needs a comparator, we’ll stand next to one. We think that is the honest position for a company of our size, and it is usually the fastest way to be useful.
We also work alongside existing specialists rather than displacing them — including in areas we’ve deliberately chosen not to enter.