One pipeline from pixels to production
Ingest any camera, train on your data, and deploy the same model artifact to the edge or the cloud. No glue code, no MLOps sprawl — just a vision system that ships and improves itself.
The Foveo pipeline
Deploy anywhere. Same model.
Train once, then target the edge for latency and privacy, or the cloud for scale and batch. Switch with a flag.
Edge
- ▸Sub-10ms latency on NVIDIA Jetson, Intel, and ARM
- ▸Runs fully offline — no network dependency
- ▸Video never leaves the device for privacy
- ▸OTA model and firmware updates at fleet scale
Cloud
- ▸Elastic batch processing for archives and backfills
- ▸Auto-scaling inference for thousands of streams
- ▸Central training, evaluation, and model registry
- ▸Managed or bring-your-own VPC deployment
Label less. Ship faster. Improve forever.
Foundation models auto-label your footage; you correct edge cases in the browser. Every production correction feeds an active-learning loop that retrains and redeploys without a data-science team.
- ◇Auto-labeling — foundation models pre-annotate footage in seconds
- ◇Human-in-the-loop — browser review queues for edge cases
- ◇Active learning — production corrections trigger retraining
- ◇Versioned models — compare, roll back, and A/B in one click
Fits your stack
Stream in, push events out — over the protocols your systems already speak.
Engineered for the line, not the lab
Deterministic latency, offline resilience, and enterprise security from day one.
Security & compliance built in
SOC 2 Type II, role-based access, on-prem and air-gapped options, and on-device anonymization for privacy-sensitive deployments.