A human-in-the-loop workflow that aligns requirements, collection, annotation, review, validation, and delivery—with clear checkpoints for your team along the way.
Each project is scoped around its own modality, risk, and quality bar. The stages below are connected checkpoints—not a one-size-fits-all production promise.
We define the intended use, data type, class taxonomy, edge cases, acceptance thresholds and delivery schema with your team.
Collection sources, participant requirements, consent terms and recording protocols are agreed before data capture. Calibration can use a scoped pilot where appropriate.
Project contributors apply calibrated guidelines across the agreed modalities, labels and output schema.
Reviewers check consistency, completeness and guideline adherence, escalating uncertain items instead of guessing.
Senior QA reviews escalations, recurring error patterns and the agreed quality samples.
Validate data structure, metadata, acceptance criteria and client feedback before final handoff.
Structured output ships in your preferred schema — COCO, Pascal VOC, custom JSON, or your internal format — on a cadence you set.
Agree on useful progress and review reporting for your project before work begins.
Define communication cadence, review checkpoints and escalation contacts during project planning.
NDA support and project-specific data handling and delivery requirements can be discussed before transfer.
Discuss whether a pilot batch is a suitable way to calibrate the workflow against your data.