02 / built around your problem
Custom Data
Your environment. Your constraints. A dataset that fits.
Start with the behavior you need to observe. Together we define the environment boundary, available actions, failure taxonomy and acceptance checks before generating data.
Delivery can include environment definitions, task specifications, state transitions, recovery trajectories, deterministic verifiers and provenance. The scope is agreed for each project.
Continuous Data extends an agreed dataset with versioned, recurring deliveries. Each addition follows the same acceptance gates; volume never substitutes for evidence.
WHAT AN ENGAGEMENT LOOKS LIKE
- Problem
- Generic training examples miss your environment and failure modes.
- What we produce
- A scoped private dataset with agreed tools, states, failure taxonomy and quality gates.
- What you provide
- Your schema, environment, mechanics, action space, failure modes, evaluation criteria and delivery requirements.
- What you receive
- Versioned accepted records, schemas, provenance and acceptance evidence.
- Problem
- A changing agent or environment needs consistent additions to its data.
- What we produce
- Recurring, versioned additions under an agreed acceptance protocol.
- What you provide
- A validated baseline, change priorities and a delivery cadence.
- What you receive
- Incremental releases, change summaries and QA for each delivery; volume is agreed, not promised.
