Vision · Drones
Aerial detection trained in simulation
Detection networks trained inside a drone-flight simulator (software-in-the-loop) to generate labeled aerial data at scale, then prepared for deployment on real aircraft for public-safety work.
Custom machine learning
We train custom models end to end—data pipelines, GPU training, and deployment on cloud, edge, or embedded hardware—and we prove they work on your data before you scale them.
Is it a fit?
A neural network does two jobs: it recognizes patterns people can’t see at scale, and it compresses a hard decision into something fast and repeatable. If you have a high-volume decision, a sensor or document stream, and a measurable cost for getting it wrong, there is likely a model worth building.
Representative work
Client work is anonymized. Figures come from our own evaluations.
Vision · Drones
Detection networks trained inside a drone-flight simulator (software-in-the-loop) to generate labeled aerial data at scale, then prepared for deployment on real aircraft for public-safety work.
Vision · Inspection
On-board defect detection on commercial drones with a bolt-on edge computer: consistent standoff capture and before/after comparison between flights.
Vision · Logistics
Edge computer vision that reads barcodes and printed labels on inbound pallets, with multi-frame consensus for shrink-wrapped and damaged labels.
Healthcare
Modeling that supported federal certification of a continuous room-sanitation device, indicating about 80% lower cumulative exposure than spot-cleaning.
Finance
A research agent that scored 100% (246/246) on OfficeQA—grounded reasoning over 89,000+ pages of Treasury Bulletins.
Quantitative
A nightly loop proposes one change, tests it against a calibrated noise floor, and promotes only net-positive candidates—with every decision logged.
How engagements work
Every stage is quoted as a fixed fee, capped at the amount shown in your proposal, and broken into milestones you can pay against. If a stage doesn’t hit its agreed metric, you decide whether to continue.
We audit your data, define the metric that matters, and measure a baseline. You get a go/no-go report either way.
A working model on your data against the agreed benchmark—often a first live demo within weeks.
Hardening, integration, and deployment to cloud, edge devices, or your own infrastructure.
The self-improving loop keeps running on new data; only changes that beat production are promoted.
Scope a project
We reply within one business day. Prefer a call? Book 30 minutes.