Not the people selling chatbots with your logo on it. Not the ads. Nobody — because the people who could build it aren't looking at businesses like yours. That's the job: I take one annoying part of your week, build the thing that handles it, and you decide if it's real.
Evidence
A 31-person company, 7 products, and no single view of how the operation actually fit together.
Found the biggest client trapped in the design arm instead of connected to the core platform.
A small-firm research system routed facts to source law instead of hoping search found the right statute.
100% recall on the bar exam, with source text beside the answer.
A crew counted roughly 10mm oyster seed by hand after the trade had accepted ±20% variance as normal.
Automatic counting worked in the farm pilot.
Recall, latency, throughput, error rate — pick one and I work from there. No AI for AI's sake. Starts with a $950 diagnostic. Fixed, quoted before anything starts, credited to the first milestone.
If a SaaS product would solve it, you'd have bought one. I assemble the model, retrieval layer, and integration around your data — not the demo dataset.
Founder direct. Code and weights yours to keep. No black-box subscription. No retainer trap.
Receipts
A legal AI system that found 100% of the relevant law and beat the $1,200-a-seat incumbent — about $1/month to run, built in one week on normal computers.
Verified performance · bar exam
found every relevant law on the bar exam
specific measurements taken from a single photo entirely on-device
accuracy finding and tracking dogs in real-world video
improvement over the top public AI at predicting player moves
past decisions and source context stay attached to the work
real sources found by a free local tool compared to a leading $20/mo AI
Recall, latency, error rate — every claim has a number on it. If it can't be measured, it doesn't ship.
Commercial bots charged 1% plus $2-4 per trade and still ran 2.1x to 5.3x slower. My bot landed 40.2% same-slot.
Local-first inference where it makes sense, cloud where it doesn't. You own everything — training data to deployment weights.
Problem Signals
Benchmarks, citations, latency numbers — every output traces back. No black box. No rent-forever API. Founder direct from intake to ship.
The Diagnostic
Send me the spreadsheets you already keep — the org roster, the task board, the tracking mess — and one hour on a call. Don't clean anything up. The mess is the data. In 2–4 business days from a complete intake, I hand back the one structural gap running your company, proven from your own files.
$950. Fixed, stated up front, credited toward the first build if we continue. If we don't, the diagnosis is still yours.
The most common way a diagnostic fails is a list — twelve places you "could use AI." Mine ends in one finding. If I hand you a list, I failed, and I'll say so.
Last run: a ~30-person payments company running 7 products. The owner sent two spreadsheets and gave me an hour on the phone. Overnight I found the gap — the map of how everything fit lived in three people's heads, and nothing caught the overflow. Three places where one resignation breaks the company, drawn on paper he could keep. He asked for pricing before I'd offered any.
Structure
Engage
Name the workflow. I attempt it on a fair test. You judge against your human baseline. If I lose, the check is yours. If I don't, you just found a system worth building.
