Data platforms are being used to model entire housing portfolios — identifying where investment will have the most impact before a penny is spent. Sava is helping providers like Broadland Housing and Soha Housing target retrofit programmes precisely, rather than taking a blanket approach. Kensa is deploying ground source heat pumps at scale across Thurrock's tower blocks and One Manchester's stock.

The outcomes are significant. Heating bills reduced by up to 50%. Carbon emissions cut by 70% in some programmes. For residents, this means warmer homes, lower bills, and reduced risk of damp. Coventry City Council, working with E.ON and Kestrix, is using AI-powered drone thermal imaging to create a city-wide map of heat loss — enabling targeted retrofit investment for residents most affected by fuel poverty.

The gap is between organisations using data to target and prove impact, and those still taking a reactive or blanket approach. As retrofit funding becomes more competitive and scrutinised, that difference will matter more.

Case studies

Written-up examples from UK housing providers, with named organisations and measurable outcomes.

Haig Housing Switchee
What they did

Deployed Switchee smart thermostats and IoT humidity sensors across their older housing stock to monitor conditions in real time. Moved from waiting for residents to report damp and mould to identifying risk as it builds.

Outcome

Proactive maintenance replacing reactive callouts. Maintenance costs fell. Residents reported fewer respiratory issues. Full portfolio visibility achieved without physical inspections.

Thurrock Council Kensa
What they did

Delivered a large-scale ground source heat pump programme across Thurrock's tower blocks, replacing fossil fuel heating with low-carbon alternatives.

Outcome

Significant reduction in carbon emissions and heating costs for residents in some of the most hard-to-decarbonise housing stock.

Coventry City Council Kestrix (with E.ON)
What they did

Partnered with E.ON and AI startup Kestrix to create a "Google Maps of heat loss" for the city — using AI-powered drone thermal imaging to rapidly scan and map heat loss across residential stock and identify retrofit priorities.

Outcome

Rapid thermal mapping of over 6,000 homes, identifying exactly where insulation was failing. Data-driven approach allows targeted retrofit funding for the most vulnerable residents.

Also worth reading

Further examples from the Proven Public database — not yet written up in full.

Soha Housing
Sava
View source →
Broadland Housing
Sava
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One Manchester
Kensa
View source →
Havebury Housing
Mixergy
View source →
Phoenix Community Housing
Propelair
View source →
Leeds City Council
Ener-Vate
View source →
Midlothian Council
Ener-Vate
View source →
Kingston Council
IoT Solutions Group
View source →
London Borough of Richmond
Infogrid
View source →