Instrument-verified scientific data and verifiable environments for training, post-training, and evaluating scientific AI models.
We're building the experimental data infrastructure that allows AI systems to learn from measurements, test scientific predictions, and improve through real-world feedback.
What we provide
Verified Experimental Data
NMR, LC-MS, IR, Raman, XRD, and other instrument measurements paired with scientific annotations, experimental conditions, and provenance.
Verifiable Scientific Evaluations
Ground-truth benchmarks for molecular structure elucidation, materials characterization, scientific reasoning, and experimental prediction.
Scientific RL Environments
We're developing environments where AI agents can propose experiments, receive scientifically grounded feedback, and improve their decisions across experimental iterations.
Build with experimental ground truth.
High-quality data for pretraining. Verifiable outcomes for evaluation. Experimental feedback for scientific agents.