Anthropic’s Claude Science bets on workflow, not a new model, to win over scientists
Anthropic introduced Claude Science on Tuesday, an AI workbench that gives scientists one environment to do computational research, sparing them the hassle of bouncing between
Anthropic introduced Claude Science on Tuesday, an AI workbench that gives scientists one environment to do computational research, sparing them the hassle of bouncing between databases, pipelines, and tools. To be clear, Anthropic says Claude Science is “not a new AI model and not a more capable model for biology. It runs the same Claude models already available to everyone today (including Claude Opus 4.8), with no special access and no gating.” The workbench builds on Anthropic’s October 2025 launch of Claude for Life Sciences, which essentially augmented the Claude chatbot by making it better at life sciences tasks. Claude Science is a dedicated place to do that work. he launch, announced Tuesday at an AI for Science briefing, fits into Anthropic’s broader push to be more than a model provider and to further own the operating layer for specific industries, the way Claude Code has become the operating layer for software development. Anthropic is increasingly betting its growth on vertical, workflow-level products rather than just raw model capability (which could shape how it competes, and prices, against rivals).
Here’s how it works: One main AI assistant acts as a kind of project manager for scientists. It connects to more than 60 scientific databases and comes with pre-built toolkits for specific fields, like genomics, protein structure, and chemistry. That assistant can then create sub-assistants to help split up the work, like a project lead delegating tasks to specialists, or hand work off to a custom “expert” assistant that the user has built for their own research. A separate fact-checker AI then double-checks the citations and calculations before anything goes to publication. That fact-check step matters, as more AI-assisted writing leads to fabricated citations and unverifiable stats slipping into papers. That said, it’s still the same underlying model checking itself, not an independent source of truth. Claude Science has other ways of ensuring reproducibility. For example, the workbench can generate figures like 3D protein structures and chemistry drawers alongside the code that made them. Each figure includes the “exact code and environment that produced it, a plain-language description of how it was created, and the full message history,” according to Anthropic.
The process also saves scientists time by allowing them to edit figures in plain language, prompting the agent to edit its own underlying code. Another way Claude Science can save scientists time is by running on the lab’s own infrastructure setup rather than sending data off to Anthropic’s servers. Early users are already putting this to work. Sean Whalen, a principal scientist in machine learning and functional genomics at Gladstone Institutes, used Claude Science to build a genome browser from scratch in days, according to Anthropic. Allen Institute neuroscientist Jérôme Lecoq used the tool to build a multi-agent computational review pipeline, shaving off years of human work. The Claude Science launch comes a couple of months after OpenAI came at the same problem from a different side. In April, OpenAI released GPT-Rosalind, a specialized model that is fine-tuned for biological reasoning. The difference between the two approaches isn’t only about whether a specialized model is necessary — it also comes down to who gets access, and how fast. Rosalind launched as a research preview limited to qualified enterprise customers in the U.S., gated behind a qualification and safety review.
The BriefWire