BenchSci
Free tierThe agentic AI workbench that gives every scientist a team of expert PhD scientists 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+ domain-specific scientific skills for target ID, omics, and experiment designCurated reagent data: 16M antibodies, 22M RNAi entries, 18M CRISPR records
Enterprise pricing
Toronto, Canada
Founded 2015
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Technical Integration & Setup
Platform Architecture
EMET uses a multi-layer orchestration engine:
- Decomposition layer: Breaks complex queries into sub-tasks routed to domain-specific skills
- Knowledge graph: 858M nodes, 2.2B edges, 241 edge types, 100M ontological nodes
- Model ensemble: Frontier LLMs + ESM-2 (protein), AbLang2 (antibody), RDKit (cheminformatics)
- Neuro-symbolic evaluation loop: Validates outputs for 95%+ accuracy
Data Access
- 38M+ publications: 22M open-access + 16M closed-access via exclusive publisher partnerships
- Reagent databases: 16M antibodies, 22M RNAi, 18M CRISPR records, 500K cell lines, 700K animal models
- 780K patents, 310K preprints, and 1,000+ curated Omics and scientific databases
Enterprise Integration
- Ingest proprietary and dark data (internal lab data, spreadsheets, siloed databases)
- Build customizable agentic workflows tailored to your R&D processes
- Connect to self-driving labs for closed-loop experimental automation
- Dedicated bespoke connector development by BenchSci's PhD scientific team
- Built for regulated biopharma compliance requirements from day one
Accuracy & Validation
- Validated across 600+ tests and 8+ scientific benchmarks
- 2–4x more accurate than standalone frontier LLMs on biology tasks