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External pipelines · RISE project catalogue

Claude Science

Anthropic's AI workbench for researchers ("Claude Code for science"), announced 2026-06-30: a desktop app (macOS/Linux) in which a generalist coordinating agent with 60+ curated skills and connectors spawns specialist agents to run literature analysis, database queries, multistep data analyses, figure iteration, and manuscript drafting, with compute spanning the local machine, HPC clusters via SSH, and Modal GPUs. Covers a broad slice of the RISE pipeline from literature work through manuscript refinement, in the same big-lab workbench layer as Prism and Google Co-Scientist.

Indexed in RISE · activeConformance with the standard plannedProject site

What it does

Auditable-artifact design: every figure ships with a reproducibility package (exact code, computational environment, plain-language methodology, full message history), and a background reviewer agent flags incorrect citations, untraceable numbers, and figures that don't match their underlying code as work progresses. Deepest pre-configured life-science stack of any big-lab offering — 60+ databases (UniProt, PDB, Ensembl, ChEMBL), NVIDIA BioNeMo Agent Toolkit, Evo 2, Boltz-2, OpenFold3 — backed by a grants program of $30,000 in credits for up to 50 AI-for- science projects (applications closed 2026-07-15).

Focus
end-to-end
Inputs
research-task-prompt, user-datasets, custom-skills-connectors
Outputs
analysis-artifacts, reproducibility-packages, figures, manuscript-drafts
Architecture
multi-agent, tool-use, persistent-memory, iterative-loop, artifact-versioning
Maintained by
Anthropic
Started
2026

Description

Data model
Discipline
General
Method family
not specified
Design
not specified
Research stage
Literature discoveryLiterature synthesisResearch designData acquisitionData analysisCode generationDraftingRevision and editing
Contributors
Anthropic
Usage
not used in published research yet
Source
RISE project catalogue · projects/landscape · @4c17bae
Record
pipeline:claude-science · JSON

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Bring it into the standard

A pipeline built outside E2ER can meet the standard by describing its steps as a template, attaching the floor of checks and publishing evaluation records. Its authors keep ownership and credit.