Solutions / Foundation Model Builders
Frontier labs & pre-training teams
Data that moves the capability frontier — not just the loss curve.
Once a base model saturates public benchmarks, progress depends on the quality of the supervision signal, not its volume. Frontier teams need expert demonstrations, calibrated preference data, verifiable reasoning, and uncontaminated private benchmarks — produced fast enough to keep pace with training runs.
AI use cases
Where it applies.
- Post-training alignment
- Expert reasoning demonstrations
- Preference & DPO data
- Red teaming and safety
- Private benchmark design
- Capability gap analysis
Data requirements
What it takes.
- Domain-expert authored data
- Rubric-calibrated judgments
- Uncontaminated evaluation sets
- Reasoning trace verification
- High inter-annotator agreement
- Fast iteration on data specs
Relevant data products
Products that map to this work.
Workflow
How the program runs.
- 01Capability Scoping
- 02Rubric Design
- 03Expert Production
- 04Multi-layer QA
- 05Evaluation
- 06Iteration
Continuous loop — outputs feed back into the data engine.
Quality & compliance
Built for regulated, high-stakes work.
Every engagement runs on our quality system and enterprise-grade security workflows — the controls an auditor would expect.
- Customer-owned training data
- Data lineage and versioning
- NDA and secure workspaces
- Benchmark leakage controls