Frontier Alignment
Expert demonstrations, reasoning traces, and human preferences that help capable models become more useful, reliable, and aligned.
- Expert-written demonstrations and structured reasoning examples
- Human preference comparisons and task-specific rubrics
- Adversarial prompts and safety-focused review
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Agentic AI
Human-led trajectories, realistic task environments, and deep evaluation for agents that need to act, adapt, and complete real work.
- Human-demonstrated tool-use and computer-use trajectories
- Task design with clear goals and success criteria
- Agent failure analysis and contextual evaluation
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Multimodal & Speech AI
Language, voice, image, and video data with the context models need to connect what they see, hear, and understand.
- Speech transcription, conversational audio, and TTS review
- Image-language annotation and video action labeling
- Multilingual quality checks and voice-agent evaluation
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Physical AI
Egocentric recordings, sensor annotation, and human demonstrations that connect embodied systems to the complexity of the physical world.
- First-person activity data and embodied demonstrations
- LiDAR, multi-camera, and sensor annotation
- Interaction sequences for robotics and world-model development
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Model Integrity
Human evaluation that investigates hallucinations, bias, and failure modes—turning uncertain model behavior into clearer quality signals.
- Hallucination, bias, and failure-mode assessment
- Human evaluation against explicit quality and safety criteria
- Repeatable test sets and review of edge cases
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Research Services
Expert-designed benchmarks, calibrated judging, and carefully reviewed synthetic data for teams exploring the next frontier of AI.
- Custom benchmarks built around real research questions
- Calibrated model judging with human review
- Synthetic data development and expert quality checks
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