BLT AI didn’t learn construction from the internet. It learned it from receipts photographed at supply house counters, hours clocked in at 7 a.m., roof decks shot before the drywall went up, and budget lines that went over — millions of small interactions from real jobs, each one a fact about what building actually costs.
Cumulative across all BLT projects. Figures update monthly.
A receipt photographed, an hour clocked, a purchase request approved, a phase closed, a budget line moved and the reason someone typed for moving it. Each one is written to an append-only stream with a timestamp, an actor, a project, and a phase. Nothing is a snapshot; everything is a sequence.
Illustrative stream. Real events carry the same shape.
BLT AI is not one model answering questions. It is a set of readers and comparers that run continuously against the stream, each with a narrow job and a clear output.
Reads receipts, invoices, and statements down to the line item. Quantities, units, SKUs, tax. Assigns each line to a project, a phase, and a category, and keeps the photograph alongside so a human can check the machine.
Checks every frame the crew uploads against safety and quality patterns. Fall protection, house wrap below grade, exposed conductors, standing water, debris on a deck. A flag carries the reason in plain language, never a score.
Holds what each phase has actually cost across every build that closed — by market, by plan, by square foot, by crew. This is the memory that makes “38% above comparable” a fact instead of a feeling.
Runs the live stream against Baseline continuously. Pace, committed exposure, variance against the estimate a line was raised under. It speaks when a number stops making sense, not on a schedule.
Reads everything that happened since you closed the laptop and writes the brief you’d have written if you had time. What moved, what’s waiting on you, and what needs a photo before the inspector arrives.
Plain-language queries against your own transactions. “What did we spend on plumbing?” “Average cost per square foot for foundation work?” It answers from the ledger and shows the rows, so you can check it.
Most construction software forgets a job the moment it closes. BLT keeps it, because a closed phase with real actuals against a real scope is the most valuable thing a builder produces and almost nobody keeps it in a form a machine can read.
The crew photographs, clocks in, and raises requests. Ten seconds each, on the phone already in their hand.
Extract and Vision turn paper and photos into coded lines and flagged frames, with the source kept alongside.
Signal runs the live job against Baseline — this phase, this market, this plan, against everything that closed before.
A claim with its arithmetic and one thing to do. The decision stays with the human; the arithmetic doesn’t.
The phase locks with real actuals against real scope, and becomes the expectation the next build is measured against.
Not a national average and not last year’s markup. What framing cost on comparable lots in your market with your crews, at the prices you actually paid. Lumber moved between the bid and the buy on almost every job in the last three years — the only defence is a memory that holds real numbers with real dates on them.
Photos carry hours and phases, so BLT sees the real order of operations — how long roof deck takes after framing, how often rough-in waits on an inspection, what a rain week does to the three phases downstream. That’s what makes a drafted schedule worth looking at.
A safety flag that sat unassigned for four days. A phase with no photos during active work. A line item raised against an estimate it exceeded by $1,180. These are visible in the stream days or weeks before they become a number on a report, and they are the same handful of patterns on almost every build.
Your projects, your costs, and your vendor pricing are visible to your organization and nobody else. Cross-project comparison runs inside your own account first — this lot against your last three, not against a competitor’s.
Where BLT learns across the platform, it learns shape rather than substance: that a phase like this tends to run long, that a photo like this usually means a missing detail. Never your line items, your margins, or who you buy from.
Every event carries an org, a project, and an actor. Nothing crosses that boundary without you moving it.
Expenses, budget history, photos, and reports export as CSV and a media archive. We don’t hold your data hostage.
Free on one project, full AI. Your first closed phase is the one that starts making the next estimate honest.