Features
Verifier-grounded data generation using formal proof systems
Simulator-based synthetic data generation
Executable test-driven data validation
Oracle database integration for trustworthy data
Information-dense natural language supplements (physics, biology, logic)
Batch integrity verification via SHA-256
Custom data generation for LLMs, image, video, and speech
Selective engagement model for high-impact projects
Pilot conversation initiation available
Data integrity per batch displayed on website
Reverse-engineer causal mechanisms of AI models
Reveal internal structure and hidden representations
Detect performative chain-of-thought in LLMs
Identify confounders and debug model behavior
Validate whether models learned real clinical understanding
Trace unstable behaviors to brittle internal features
Reduce hallucinations via features as rewards
Accelerate materials discovery with self-correcting search
Control training precisely with less data and off-target effects
Support for LLMs, life sciences, and robotics/vision models
Harvest activations from trillion-parameter models
SOC 2 Type II certified security and compliance
Analyze latent policy structure in robotics models
Interpret genomic models like Evo 2
Discover novel biomarkers via model reverse-engineering
