Benchling
Cloud R&D platform for biotech labs with electronic lab notebook, sequence tools, and AI
About Benchling
Benchling is a cloud-based life sciences R&D platform that combines a collaborative electronic lab notebook (ELN), molecular biology tools for designing and tracking DNA and protein sequences, and a registry for managing samples, reagents, and inventory. It connects notebook, registry, sequence design, and workflow/LIMS modules so data flows between them without manual re-entry, and layers in AI tools that design experiments, guide lab execution, capture structured results, and recommend next steps. It targets biotech and pharma R&D teams across discovery, pre-clinical, and process development, with permissioning, audit trails, and validation support for GxP and FDA-regulated environments.
Screenshots
Commonly Cited Strengths & Limitations
Strengths
- Broad connected platform spanning notebook, registry, sequence design, and workflow/LIMS
- Data flows between modules without manual re-entry
- Widely adopted in biotech R&D informatics
- Mature ecosystem of integrations and APIs for lab instruments and other software
- Built for GxP and FDA-regulated environments
Common Use Cases
- Designing genetic constructs and plasmids
- Documenting experiments for regulatory audit or internal review
- Tracking samples through automated pipelines
- Managing lab inventory and reagents
- Recording R&D data in cell and gene therapy, synthetic biology, and biologics
- Designing, registering, and characterizing proteins and antibodies
- Accelerating in vivo studies with modern data capture and collaboration
- Process development R&D (bioprocess)
- Automating, managing, and analyzing instrument data at scale
Details
- Pricing Model
- Contact Sales
- Team Size
- Small Business, Enterprise
- Category
- AI & Machine Learning
Key Features
- Collaborative, cloud-based electronic lab notebook (ELN) to plan, record, and share experiments
- Automated workflows and analytics to reduce manual, repetitive work
- AI tools including the AI Scientist that design experiments, guide execution, and recommend next steps
- Scientific data modeling for biomolecules, small molecules, cell lines, animals, and reagents
- Unified data model across experiments to power computational science
- Molecular biology tools for DNA and protein sequence design and tracking
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