Why Inspectr
Everyone has access to the same models. What makes AI useful in a building is context: the assets, history, standards and decisions behind the work. Inspectr owns that context and does the work across your systems, built alongside the teams running 105M+ sq ft.
What goes in
The AI layer
Inspectr
Live building context
What Inspectr knows: every asset, system, record and document you connect, in one live picture.
Specialized agents
Agents that own a workflow end to end and deliver where the work already lives.
Activity Center
Where your team reviews, approves and controls anything consequential.
Operating memory
What Inspectr learns: your standards, thresholds and decisions, applied from then on.
What comes out
Give both the same ticket and the difference is not the reasoning. It is everything each one can see before it reasons.
Generic AI sees
Everything else has to be typed in, and everything it returns has to be checked, corrected and finished by your team.
Inspectr sees
And then it acts
Fast output is not the same as finished work.
That gap — between generated output and work your team accepts — is where most AI programs stall. Closing it means connecting fragmented systems, holding real building and asset context, and working inside the workflows your team already runs.
Copilot-style assistants are built for one company on one shared IT stack. Building ops is many parties working across systems that none of them fully owns — stitched together by hand.
Landlord, occupier, contractors and specialists — no single organisation owns the work.
CAFM, BMS, metering and O&M documents — owned by one party, or neither.
One ticket touches the occupier's CMMS, the landlord's BMS and a contractor's engineer — bridged by manual work today.
The work crosses company and system boundaries — an assistant that stops at your tenant's edge can't reach it. The layer that does the work has to cross them too.
Internal builds sound attractive, but require more than access to a model. Teams need AI product capability, domain expertise, integrations, workflow design, model orchestration, security reviews, and a path to production value.
High control. Slow path to value.
Generic AI tools give teams output, but not context. They do not understand your buildings, assets, vendors, work order history, or standards — so every result still needs to be checked, corrected, and finished by your team.
Fast output. Slow path to finished work.
A dedicated partner gives you the AI layer across your building systems without starting from zero. Inspectr brings AI product capability, facilities and asset management context, and operating workflows together in one platform — with hands-on delivery behind it.
Fast path. Domain-specific leverage. Outcomes on the invoice.
Four things, built specifically for the teams responsible for building performance: owners, operators, service partners, and facilities and asset management leaders.
Domain context is native.
Assets, systems, work orders, PM programs, vendors, SLAs, standards and compliance are first-class concepts — not something your team re-explains in a prompt every time.
Agents produce finished outputs, not recommendations.
A diagnosis arrives as a job plan. A condition change arrives as a revised reserve. A miss arrives with the evidence already assembled — written back to the system that holds the work.
Building context deepens. Operating memory grows.
Every closeout enriches the equipment record. Every correction becomes the standard the next run follows — one engineer fixes a useful life once, and every capital plan carries it.
Your best people teach the system; the system hands it to everyone else. New hires inherit it, and it stays when people leave.
Automatic where safe. Approval where consequential.
You set the level for every action. Nothing is a black box: each one records what triggered it, what it did, who approved it and what happened after, reviewable in the Activity Center.
Behind all four: hands-on delivery, model orchestration handled for you — the right context, workflow and model applied to each task without expensive trial and error — and pricing tied to measured outcomes.
Inspectr is not a generic AI wrapper. It is built around the real work of facilities and asset management: tracking assets, understanding maintenance history, surfacing risk, generating plans, diagnosing work orders, analyzing performance, and keeping operational outputs current.