The Operating System for Physical AI
Build the Nervous System for Robots at Planetary Scale
Cerebric unifies data capture, training, and deployment so robotics teams can go from raw experience to reliable autonomy—faster than anyone else.
Trusted by researchers and operators from
One platform, the entire robotics lifecycle
From ingesting raw sensor data to deploying robust policies in the field, Cerebric turns every mission into compounding intelligence.
Data Collection
Capture every interaction with synchronized multi‑sensor recording and rich metadata.
Data Management
Normalize, index, and curate petabytes of robotics data for rapid reuse.
AI Training
Train foundation models with repeatable pipelines and built‑in evaluation loops.
AI Deployment
Ship models to fleets with safe rollouts, monitoring, and edge‑cloud inference.
From raw telemetry to a robotics data marketplace.
Ingest, store, and index petabyte‑scale datasets from labs, fleets, and partners. Build a living Data Bank where every run compounds future performance.
- • Multi‑modal ingest with time sync
- • Privacy‑safe sharing and licensing
- • Dataset versioning and lineage
See every failure before it ships.
Replay and inspect data at scale. Identify edge cases, annotate precisely, and create targeted training slices without brittle scripts.
- • High‑speed playback
- • Queryable slices by scenario
- • Collaborative review workflows
Train, evaluate, and iterate in days, not months.
Cerebric standardizes pre‑training and fine‑tuning for robotics. Run experiments, compare policies, and ship the best model with confidence.
- • Distributed training at scale
- • Integrated evaluation harness
- • Model registry and governance
Deploy intelligence across every robot you own.
Push optimized weights to fleets, balance compute between edge and cloud, and monitor performance in real time.
- • One‑click fleet deployment
- • Hybrid inference orchestration
- • Continuous feedback loops
The robotics data flywheel starts here
Capture more experience, train better models, and deploy safer autonomy—at enterprise scale.