Sentinel watches the feed, geolocates every detection, reasons across frames, and drafts the report — before the mission is over. Operators get a decision-ready answer in the form they can act on.
.svg)
Sentinel behaves as an agent: working memory, tool use, a SALUTE-style changelog, and citations back to the evidence it reasoned from.
Four-level geolocation fallback — telemetry, derived, sensor-inferred, frame-center — so every detection resolves to a lat/lon with operator-trustworthy confidence.
Describe the mission, the entities, the reports you want out. Sentinel pulls the right skills from its library — detection, tracking, change detection, defect classification — and sets itself up. New deployment, same system underneath, configured in plain English.
MISB-compliant KLV ingest across EO/IR, radar, and survey platforms. Plug into what you already run.
SALUTE reports, condition summaries, and change reports drafted before the operation is over. Every claim cites the evidence it came from — auditable end-to-end.
Cloud, on-prem, or edge hardware when the network isn't an option — including Jetson-class devices. Plugs into the systems operators already run: Firestorm, CoT, GIS, BIM, CMMS.
Sentinel triages ISR feeds in real time, flags the frames that matter, geolocates every entity, and drafts SALUTE reports before the mission is over — freeing analysts to decide instead of scrub.
Sentinel watches the drone footage, identifies defects against the relevant standard, and drafts the condition report. Your P.E. reviews and signs. One human in the loop, at the signature line.
Sentinel adapts to space-grade sensors and orbital imagery; Seahaven generates the scenes real data hasn't shown the model — rendezvous, debris, surface change, on-orbit anomalies. Long-dwell observation, without the ground-link bottleneck.
Warehouse, yard, mine, manufacturing — the settings where edge cases outnumber the normal ones. Sentinel's pipeline handles the long-tail; where the real world hasn't shown enough examples, Seahaven fills the gap.
Seahaven is Lexset's parametric 3D engine — photorealistic, fully annotated training data generated on demand. It is its own product: enterprise CV and ML teams use it directly, whether or not they ever touch Sentinel.
And it's the tool we reach for when Sentinel lands in a domain where real data is thin — new sensors, rare failure modes, the long tail no one has collected. Nine years of building for the real world is why Sentinel holds up on novel scenes.
Generate datasets that used to take months in minutes. Build, train, evaluate, iterate — at software speed. Drops into PyTorch, TensorFlow, and the training pipelines your team already runs.
Every pixel is already labeled. RGB, semantic segmentation, instance masks, depth, normals, 3D poses — free, exact, by construction.
Dial the long tail. Parameter-drive lighting, materials, weather, occlusion, sensor noise. Engineer the failure modes that actually matter to your mission.
Primes, integrators, and government programs deploying perception where adversary pressure and operational tempo leave no room for lab-grade assumptions.
Utilities, tower companies, solar O&M, transmission, and the engineering firms that serve them — shipping condition reports at the pace the grid actually needs them.
Perception teams at Fortune 500 and late-stage startups who've run out of real data and need to engineer their training distribution on purpose — on Seahaven, standalone.
Defense program, enterprise CV team, utility, or integrator — if perception in the real world is what you need, we'll show you what Sentinel and Seahaven do, together or apart. Briefings are kept short and technical.
Or email us directly: info@lexset.ai
