01
Review layer included
Reasoning and coding
Complex tasks, verifiable solutions, critiques, and preference signals.
Frontier development
Data programs for the next capability frontier.
Expert data, rigorous evaluation, and fast iteration for teams training general-purpose language and multimodal models.
Signal map
Program outcomes
Novel capability data
Fast iteration loops
Model-specific evaluation
Inside the work
Human expertise, connected to a controlled data workflow.
Every engagement links the people doing the work, the evidence used to review it, and the model behavior the program is meant to improve.
Capabilities
Built to fit the model, domain, and decisions behind your program.
02
Review layer included
Multimodal intelligence
Interleaved image, video, audio, and language tasks built for genuine cross-modal reasoning.
03
Review layer included
Alignment and safety
Evaluation and feedback systems that reinforce useful, bounded behavior.
04
Review layer included
Agent capability
Realistic environments, trajectories, verifiers, and failure analysis.
What gets delivered
More than a dataset: a usable package of data, controls, and learning.
The exact artifacts change by program, but every delivery is designed to be inspectable, actionable, and ready for the next model decision.
01 / Design
Task specification
A structured task set, rubric, edge-case policy, and worked examples.02 / Data
Reviewed data batches
Versioned examples with review outcomes, rationales, and adjudication where needed.03 / Insight
Quality readout
Acceptance evidence, error patterns, and recommendations for the next iteration.Delivery model
Designed for fast learning and controlled scale.
Programs move in visible stages, with a review point before scope, volume, or complexity increases.
- 01Frame
Identify the capability frontier
- 02Calibrate
Design discriminative tasks
- 03Produce
Calibrate experts and reviewers
- 04Learn
Iterate from model failures