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Avala Academy

The Ground-Truth Loop

Aprann kijan done flòt yo bay pi bon modèl: antre done, vizyalize, mete etikèt, seleksyone, antrene, epi deplwaye. Swiv sik la depi done brit detèktè yo rive nan pwochen ansanm done a.

Kòmanse kou a
  1. 01Enjere
  2. 02Vizyalize
  3. 03Anote
  4. 04Kire
  5. 05Antrene
  6. 06Deplwaye

Deplwaye remete nan Anote: echèk sou teren an vin pwochen seri done a.

Academy

Kòmanse kou a

  1. 01

    Foundations

    What is Avala?

    Learn how Avala connects sensor data, labeling, quality review, and training-data delivery for Physical AI.

    2 min lekti
  2. 02

    Foundations

    The Ground-Truth Loop

    Follow the decisions that connect sensor recordings, reviewed labels, training data, and model evaluation.

    2 min lekti
  3. 03

    Ingest & Visualize

    Ingest & Visualize

    Prepare a supported recording, upload it as a private dataset, and check timing, calibration, and coverage before labeling.

    2 min lekti
  4. 04

    Annotate

    Annotate

    Choose labels for your model, use supported automation, and review the results against an explicit quality specification.

    2 min lekti
  5. 05

    Curate

    Curate & manage

    Choose data for a specific training goal and preserve the source, review context, and export used for the handoff.

    2 min lekti
  6. 06

    Train

    Train

    Export a reviewed project, validate the output in your training loader, and record the data and code behind each run.

    2 min lekti
  7. 07

    Deploy

    Deploy & close the loop

    Use field events and evaluation results to decide what to inspect, label, and measure in the next data release.

    2 min lekti
  8. 08

    Foundations

    Make it yours

    Connect your own workspace through the documented SDK, CLI, and MCP interfaces, starting with a read-only request.

    2 min lekti