Built by someone who has spent years in the field — and a year in the AI lab.
Construction projects fail for predictable reasons: billings that don't match installed work, schedules that slip quietly until they don't, and site conditions that nobody documents until there's a dispute. The data to catch these problems early exists — photos, schedules, pay apps — but nobody has time to connect the dots.
Over the last year I've been building and testing AI tools specifically for this gap. Using vision language models like Qwen VLM, I've developed workflows that can look at a jobsite photo and tell you what's been installed, cross-reference it against the schedule, and flag it against the billing — in seconds.
Construction data is sensitive. I don't want your project data sitting on a server somewhere. The tools on this site process your uploads in real time and return results immediately — nothing is stored, nothing is trained on your information. Your data stays yours.
The live demos on this site are the proof of concept. The goal is a lightweight AI co-pilot that any project manager can use — no data science background required, no expensive software subscription, no IT department needed.