Research needs faster iteration, so we built SilicoLabs, not more ideas.

The challenge we address

Drug discovery and protein engineering often occur without a dedicated computational chemist or bioinformatician. When a researcher has an in-silico hypothesis to test, the choices are to set up and run the computation yourself, spending weeks getting up to speed; submit it to a core facility and wait weeks in line; or abandon computational validation and synthesize without it.

Each path has a cost. Synthesis first spends reagent budget on candidates that a 10-hour simulation would have deprioritized. Core-facility queues add six weeks to a research cycle, while DIY computation becomes a full-time job.

SilicoLabs handles the middle layer: its agent reads a scientific question in natural language, selects and configures the right computational method, runs the job on distributed compute, checks convergence, and returns results a biologist can read and use. No installation, parameter tuning, or queue.