Construction QA software

The problem is not that nobody knows the standards

You know what a correct expansion gap looks like. Your lead knows. The issue is that neither of you can be standing in forty bathrooms at once, and the photos that would have told you sit in a group text until the homeowner calls. By then the tile is grouted, the crew is two towns over, and the fix costs you a day and a chunk of the margin.

Quality assurance in construction has always been a coverage problem, not a knowledge problem. Traditional QA software attacks it with checklists, which only works if somebody fills them in honestly at the end of a long day. Supervisr attacks it from the other side: the photo is the checklist. Every photo that gets uploaded is reviewed automatically, whether anyone remembered to review it or not.

How a photo actually gets graded

Each photo is matched to its trade and run against a model grounded in that trade's industry standards — tile against tile standards, roofing against roofing, drywall against drywall. Coverage is live across every trade rather than one flagship category, because a remodeler's camera roll is never one trade deep.

The result comes back in two kinds, and the distinction is the whole design:

• Flags — something that needs a human decision. A missing expansion gap, lippage past tolerance, a flashing path that will not shed water. These route to a person.
• Notes — an observation worth recording that is not a defect. These file themselves into the job record and become the evidence that the work was right.

Most tools only ever produce the first kind, which is why crews learn to ignore them. A system that only ever tells you what is wrong is a system your foreman stops opening.

Tuned to your crew, not to a demo

A punch-list standard that makes sense on a high-end gut renovation will bury a production crew in noise on a rental turn. So the analysis is calibrated on several axes you control:

• A sensitivity setting you move yourself, so the flag threshold matches the work you actually sell.
• Project-type calibration — the same photo is judged differently on a custom build than on a turn, because it should be.
• Customer-supplied material awareness, so your crew never takes a flag for a tile the homeowner picked and delivered short.
• Field-Manager-aware routing — a flag goes to whoever actually owns that job, not to a company-wide inbox nobody is responsible for.

What the QA output turns into

A grade on a photo is only worth something if it moves through the business. The same analysis feeds the rest of the account:

• An open-flags queue per job, so a walkthrough starts from a list instead of a memory.
• Client reports built from verified work, shared from your own phone and your own number — Supervisr never contacts your customers.
• Closeout evidence that lives with the job forever, which is what you reach for the day a warranty claim shows up.
• Marketing drawn only from work the engine already verified, so nothing goes out that you would not want a prospect to inspect.

And because it all hangs off the photos, the back office fills itself in as a side-effect: schedules, work orders and POs, bids and e-sign, monthly financials, receipts. The full list is on the contractor features page.

Honest about what it is

This is an AI reviewing a photograph. It is very good at catching the recurring, costly, visible misses — the ones that generate callbacks — and it is not a licensed inspection, an engineering assessment, or a code-compliance review. It is there to protect your reputation by catching what a busy human missed, and to document your quality so you can prove it later. Treat a flag as a reason to look, not a verdict.

Run it on a job you already finished

The fastest way to judge construction QA software is to point it at work you already know the answer to. Take three photos off your last job, run them through the free tool, and see whether it finds what you found. No signup, no card.