Understand
Define the model objective, target task, environment, embodiment and data requirement.
How We Work
From requirement to training-ready data.
A controlled six-step method turns a model objective into an executable collection program, documented delivery and evidence-led iteration.
Design
Engineer the protocol, taxonomy, modalities, participants and acceptance criteria.
Execute
Execute and coordinate field operations, participants, equipment, and in-process quality control across the required environments.
Validate
Review data against quality, completeness, rights and compliance criteria; reject or rework where needed.
Deliver
Prepare structured files, metadata and documentation for customer integration.
Improve
Use customer and model feedback to refine subsequent collection and delivery.
Reviewable outputs
Every phase closes with evidence and a decision.
The next commitment begins only when scope, ownership and acceptance are clear.
- 01Discovery brief and feasibility assessment
- 02Data specification and task taxonomy
- 03Rights, privacy and supplier review
- 04Collection protocol and quality plan
- 05Validation, rejection and rework record
- 06Accepted delivery package and iteration brief
Controls shared by every data program.
Named scope and accountable project lead
Confidentiality, IP and data-rights boundaries
Qualified collection resources
Measurable quality and acceptance criteria
Milestone, risk and change control
Documented delivery and feedback loop