BenchSci
Free tierThe agentic AI workbench that reasons through disease biology for preclinical R&D
Enterprise·Technical·Powered by Multiple (frontier LLMs + ESM-2, AbLang2, RDKit)·API available
Key strengths
Access to 16M closed-access papers via exclusive publisher partnershipsProprietary knowledge graph with 858M nodes and 2.2B relationship edges95%+ accuracy via neuro-symbolic evaluation, 2–4x better than frontier LLMs100+ proprietary scientific skills covering preclinical R&D workflowsCurated reagent & biology data: 16M antibodies, 22M RNAi entries, 18M CRISPR records
Enterprise pricing
Toronto, Canada
Founded 2015
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- Target identification & validation: Automatically aggregate multi-omics, literature, and database evidence to rank and validate novel disease targets with traceable confidence scores
- Hypothesis generation: Decompose complex biological questions across 858M-node knowledge graphs to surface non-obvious mechanistic hypotheses for drug programs
- Omics data analysis: Apply specialized scientific skills to analyze transcriptomics, proteomics, and genomics datasets in the context of disease biology
- Experiment design assistance: Recommend validated reagents (antibodies, RNAi, CRISPR) and experimental protocols sourced from curated, PhD-reviewed data
- Self-driving lab connectivity: Integrate EMET's agentic workflows with lab automation systems to close the loop between computational predictions and wet-lab execution
- Proprietary data unification: Ingest and query internal dark data alongside public literature to surface insights locked in siloed spreadsheets or internal reports