AI-native data-production infrastructure for biology.
A common data model, enabling datasets alignment and benchmarks, a network of autonomous wet labs, tightly integrated with foundation models, producing at scale the structured biological data that AI-driven discovery requires.
Autonomous wet labs
Standardised modular end-to-end platform. Continuous robotised experiments with gate-by-gate decision trace, full provenance, complete metadata, environmental context, QC and re-runs.
Open access
API-in: experiment parameters & constraints. API-out: structured data, thinking traces, experiment metadata. First node opens in London. Second node to open in SF.
Experimental intelligence
Model defines cascade gates, assay menu, cell system, perturbation, gene panel, etc… and reads data and results in real time. Better data improves the models; better models design better experiments.
Get in touch.
Substrate is hiring, onboarding partners, and talking to researchers and AI labs who need experimental capacity that keeps pace with their models.