Anthropic Launches Claude Science, an AI Workbench for Researchers with 60+ Preconfigured Skills

Anthropic released Claude Science on June 30, 2026, an AI workbench designed specifically for scientific researchers. The application integrates more than 60 scientific databases and specialized toolkits into a single interface, allowing users to analyze literature, run multi-step analyses, create charts, and draft manuscripts.

Claude Science uses existing Claude models, including Opus 4.8, and includes a verification agent that automatically checks citations and calculations. The app runs locally on macOS or Linux and can connect to remote machines through SSH or HPC clusters, ensuring sensitive data never leaves a lab's own infrastructure.

Preconfigured Skills and Nvidia BioNeMo Integration

The workbench ships with over 60 preconfigured skills covering fields such as genomics, proteomics, and cheminformatics. It taps Nvidia's BioNeMo agent toolkit, which includes models like Evo 2, Boltz-2, and OpenFold3. Researchers can also save their own pipelines as reusable skills.

• Basecamp Research is making its EDEN models available through Claude Science for tasks such as designing antibiotic peptides and predicting vaccine targets from simple text prompts.
• In a demo, Basecamp co-founder Oliver Vince uploaded a sample patient microbiology report and used natural language to generate analysis.
• Results from such AI-driven designs still require laboratory testing before clinical use, according to Basecamp.
• Claude Science scales from a single GPU to hundreds when a job demands more power.

Availability and Research Credits

Claude Science is available in beta for Pro, Max, Team, and Enterprise users. Anthropic is also backing up to 50 research projects with up to $30,000 in credits each. Applications for the credit program are open through July 15, 2026.

The launch marks Anthropic's biggest push yet into the laboratory environment. By keeping data on local infrastructure and offering a verification layer, the company aims to address concerns about accuracy and data privacy that have slowed AI adoption in scientific research. What comes next will depend on how quickly labs adopt the platform and whether the verification agent can reduce the manual checking that currently consumes a large portion of researchers' time.