Computer vision, multimodal AI, and AR guide the installer through the work in real time — verifying the highest-consequence steps on the spot and sealing a time-stamped record before the crew leaves.
Failed installs are expensive, hard to attribute, and invisible until there is a claim. Today there's no record of what happened on site.

Homeowner submits site conditions and photos via email or SMS before the job. No app to download, no friction.

Highest-consequence photos verified by computer vision. Adjustments suggested on the spot. Faces blurred on capture.

Time-stamped, sealed proof bundle. Defensible attribution for every claim, return, and warranty event.
Errors are corrected on-site, not on a return visit. Job briefs and on-site guidance cut rework before it happens.
Verified photos settle payment and cut disputes. Time-stamped records push claims to the OEM or installer where they belong.
The same verification layer holds every crew to one standard — across markets, vendors, and contractor networks.
Address-level install history powers replacement timing, cross-sell, and service-plan attach long after the crew leaves.
Told exactly what to capture next — and re-shoot before they leave if it won't hold up.
Torque specs, configuration, what the standard requires — answered from the SOP and prior installs, hands-free.
The knowledge base carries the tricks and fixes flagged by crews who hit the same job before.
Time-stamped and signed per checkpoint — QA reviews exceptions, not every job.
One link resolves a claim or return with defensible proof of what was done, when, and by whom.
Installer performance and failure modes by SKU — so the next install benefits from the last.
Who, what SKU, which checkpoints, verified by computer vision, time-stamped and attributed. Embedded into your existing FSM and installer surfaces.
Serial entrepreneur with 15+ years of experience launching startups with large corporations. Former President of UP.Labs and Partner at BCG, where she built physical world businesses in spaces such as logistics, supply chain, and payments.
Researcher-turned-founder working at the intersection of computer vision, augmented reality, and AI. Previously built technology for image-guided medical procedures and surgical navigation at Medivis. Ph.D. in Computer Science from UC San Diego.