Production robot data built for deployment-grade models.

Telepath turns daily robot execution into a repeatable production data program. Instead of occasional data captures, teams get continuous traces from real workflows and measurable delivery quality.

What this program enables

Continuous production capture

Generate recurring data from real tasks instead of relying on periodic collection sprints.

Operationally grounded labeling goals

Scenario priorities come from actual workflow constraints and failure patterns, not abstract benchmark assumptions.

Lower integration friction

Delivery formats can align with existing ML pipelines so teams can move from ingest to training faster.

How Telepath runs this in production

Collection tied to throughput reality

Programs run in environments with real production pressure, preserving behavioral signal that often disappears in controlled capture sessions.

Governance and reporting built in

Teams get clear visibility into collection scope, batch quality, and progress against capability targets.

Phased scale with control

Start narrow, validate quality, then expand by task class or facility while maintaining program consistency.

Where teams usually see fastest ROI

Questions teams ask before launch

What cadence is typical for production data delivery?

Most teams run weekly or bi-weekly drops aligned to training cycles, but cadence can be adjusted to your roadmap.

Can this support cross-facility data programs?

Yes. Once quality is validated in one facility, programs can expand across sites while preserving shared standards.

How do you prevent noisy data from overwhelming model teams?

Collection scope and quality criteria are set before launch so deliveries remain targeted, usable, and tied to defined objectives.