Awaab’s Law changed the game. Your housing team is doing more compliance with fewer people.
Temporary accommodation costs at record levels. Homelessness presentations rising. Allocations still manual — housing officers matching families from spreadsheets. Awaab’s Law adding new statutory deadlines. Demand invisible until it arrives — no predictive capability.
No off-the-shelf housing AI exists. And generic tools won’t get you there.
Generic AI tools don’t understand allocations policies, TA cost modelling, or Awaab’s Law compliance timelines. Your data is siloed across housing management, homelessness, and repairs systems. The patterns are there — but nothing on the market is designed to read them.
You need AI built with your team, not configured by someone who’s never run a housing service. The domain knowledge lives with your housing officers. The technology and method live with us. Neither one works without the other.
Nobody’s done this yet — we build it with you, on your platform, you keep it.
The proven pattern
This is the same model that built every AI agent. The EHCP Agent started inside one council and is now live in 40. Needs Assessment Agent was co-created with social workers at Wigan — that council went on to score the highest CQC rating in England (95 out of 100). Minutes Agent was built with committee officers and is now in 10+ councils.
The pattern is the same every time: start with the practitioners, build on their platform, prove it in live service, then scale. It works because the people who do the job shape the tool.
Housing is active
Wigan co-creation sessions are underway. Housing was selected as MVP1 after “Listen Deeply” prototyping identified Awaab’s Law compliance and RSH inspection pressure as the most immediate drivers. The work is happening now.
Opportunity areas
TA matching
Matching families to suitable temporary accommodation considering needs, location, cost, and availability.
Demand prediction
Modelling homelessness demand before it materialises, using patterns in your own data.
Allocations optimisation
Optimising allocations against policy criteria, reducing manual matching and improving outcomes.
Let’s be honest: there is no live housing AI product today. This is new ground. The method is proven — the domain is new. That’s exactly how every AI agent started.
What housing AI could look like
Imagine AI that models demand before it materialises — seeing homelessness presentations coming weeks ahead, not the morning they arrive at reception. AI that matches families to suitable properties by weighing needs, location, cost, and availability — not from a spreadsheet, but from live data across your housing stock.
Allocations optimised against your policy criteria, automatically. Awaab’s Law compliance risks flagged before they become breaches — damp, mould, and hazard timelines tracked across your repairs system without a housing officer manually chasing every case.
This is the direction. Not a product you can buy today — a product we build together, with your housing team, inside your council, on your Microsoft tenancy. You own it. You shape it. We bring the AI engineering and the incubator method.
Start with a free AI Prototyping Day.
A full-day working session for a single service area. Your team talks us through how the work actually flows. We build working prototypes over lunch. By the afternoon, 3–4 prototypes are in the room and your team is pulling them apart. No slides, no commitment, no cost.
See how the day works