Claude 3.7 Sonnet Arrives in Dedicated $45 Science Workbench

Anthropic launched Claude Science, a dedicated research environment powered by the new Claude 3.7 Sonnet (Scientific Edition). The $45-per-month platform shifts away from the standard chat interface to provide a specialized workbench with native Python execution, live citation verification, and direct integration with electronic lab notebooks.

Laboratory Workflow Integration

The platform introduces a Vision-to-Protocol capability that converts images of lab equipment or handwritten notes directly into structured JSON or Markdown. For data workflows, Claude Science includes an optimized Python environment pre-loaded with scientific libraries like NumPy, SciPy, Pandas, and RDKit.

Outputs can sync directly to electronic lab notebooks including Benchling and LabArchives. If you build programmatic agents, this native execution environment reduces the need for external scaffolding and local compute environments.

Verification Engine and Benchmarks

To address citation hallucination, Anthropic integrated a Citation & Grounding engine. This system performs live, API-based verification against a database of over 200 million peer-reviewed papers across PubMed and ArXiv to validate DOI numbers before generating responses.

The underlying Claude 3.7 Sonnet (Scientific Edition) utilizes a customized reasoning trace tuned for chemical synthesis, genomic sequencing, and mathematical proofs. In benchmarks, Claude Science scored 84.2% on GPQA (Graduate-Level Google-Proof Q&A), an improvement over the 76.5% baseline set by the standard Claude 3.5 Sonnet.

Internal testing showed a 35% reduction in bioinformatics syntax errors compared to previous models. The system also achieved a 92% success rate in generating reproducible biological protocols without human intervention. Evaluating AI output in scientific domains requires strict accuracy constraints, and the live DOI verification attempts to automate that validation.

Pricing and Enterprise Deployment

Claude Science Pro costs $45 per user per month. This tier includes 100GB of secure research data storage and an allowance of 500 high-reasoning messages.

For universities and corporate R&D firms, Enterprise Science offers custom pricing with Virtual Private Cloud (VPC) deployment options. The enterprise tier includes a Zero-Retention privacy mode to ensure proprietary datasets are never used for model training. The platform launched with active deployments at AstraZeneca and the Broad Institute of MIT and Harvard.

If you manage compute infrastructure for research teams, evaluate whether the built-in Python environment and native ELN integrations can replace custom-built middleware. Moving heavy data analysis tasks out of standard chat interfaces and into an audited workflow provides better provenance for generated code and research outputs.