From robot video to training-ready physical-event labels.

  1. 1

    Map the source data

    We map episode IDs, camera streams, clocks, actions, and telemetry.

  2. 2

    Align the clocks

    Timing anomalies and coverage gaps are recorded.

  3. 3

    Calibrate for the corpus

    If the dataset includes physical sensors, we use them for calibration and quality checks. Otherwise, we use a corpus-specific review and validation protocol.

  4. 4

    Generate the five signals

    Each signal includes confidence and abstention. Haptica leaves a gap when the video does not support a label.

  5. 5

    Check held-out data

    Each dataset includes a quality report and known limits.

  6. 6

    Deliver the labels

    We deliver the labels as an ID-keyed overlay with a manifest, checksums, provenance, and a corrections history.

Review and QA

Review software

The review software helps inspect uncertain labels, search transitions, and verify corrections. We sell the labels.

Start with your own data.

Send the hardest hour in your dataset. We'll return a labeled sample and show you what Haptica can cover. We reply with a secure upload link.