Claude Science: The Definitive Guide to Anthropic’s AI Research Workbench

Quick Summary: What Is Claude Science?

Claude Science is a desktop application from Anthropic, launched June 30, 2026, that gives scientists a single research environment to run analyses, query databases, manage compute, and produce fully reproducible artifacts. It is not a new AI model. It runs on the same Claude models available to Pro, Max, Team, and Enterprise subscribers. Available in beta on macOS and Linux.

Scientific research has a tooling problem. A single study might require a researcher to move between PubMed for literature review, Jupyter for code, R for statistics, a cluster terminal for HPC jobs, UniProt for protein data, and half a dozen other databases, each with its own schema, query language, and interface. The friction of switching between these tools consumes time that should be spent on the science itself.

On June 30, 2026, Anthropic introduced Claude Science to address this problem directly. Claude Science is a desktop application that integrates the tools, databases, and compute resources researchers most commonly use into a single environment, with every output accompanied by an auditable record of exactly how it was produced.

This guide covers everything currently known and verified about Claude Science: what it is, what it does, how it works, who it is for, what it cannot do, how it compares to other tools, and what researchers should know before using it.

What Claude Science Is (and Is Not)

Claude Science is a desktop application, not a new AI model. Anthropic has been explicit about this distinction: the workbench runs on the same Claude models already available to subscribers, including Claude Opus 4.8, with no special model access and no capability gating beyond what those models already provide.

What is new is the environment surrounding those models. Claude Science adds scientific tooling, database connections, compute orchestration, environment management, and provenance tracking to Claude’s existing reasoning capabilities. The model provides intelligence; the application provides the scientific infrastructure around it.

Anthropic positions Claude Science as workflow software rather than a specialized biology model. That distinction matters practically: researchers evaluating Claude Science are evaluating a research environment, not a new model. The question is whether the environment adds enough value to justify using it over assembling the same components individually.

Background: Why Anthropic Built Claude Science

Claude Science builds on Anthropic’s life sciences initiative, which launched in October 2025. That initial effort augmented the Claude chatbot with improved performance on life sciences tasks. Claude Science is a dedicated application for doing that work at scale, with infrastructure that a general-purpose chat interface cannot provide.

The June 30, 2026, launch represents the most significant expansion of Anthropic’s science-focused efforts since that October 2025 start. Anthropic CEO Dario Amodei described AI’s potential in science at the launch event, stating it will serve as “a general purpose technology that helps us to make sense of that complexity, in its full complexity, better.”

Claude Science currently targets primarily life sciences researchers, which accounts for its initial database and domain configuration. The name implies broader scientific scope over time, and the hard sciences are explicitly included in the academic discount eligibility criteria.

System Requirements and Availability

 

Requirement	Detail
Operating systems	macOS 13 or later (Apple Silicon or Intel); Linux x64
Disk space	Approximately 5 GB for runtime and starter environments
Linux dependencies	socat; bubblewrap 0.8.0 or later; unprivileged user namespaces enabled by kernel
Required plan	Claude Pro, Max, Team, or Enterprise
Team/Enterprise	Admin must enable Claude Science for the organization before members can use it
Remote access	Supported over SSH or HPC login node; also available via Modal for on-demand cloud compute
Windows support	Not available at launch
Beta status	Public beta as of June 30, 2026; features subject to change

Claude Science is accessed at claude.com/science. The desktop application installs locally, with code running in a sandboxed environment on the user’s own machine. Users approve each new folder access, network host, and remote job before Claude can use it.

How Claude Science Works

The core interaction model is plain language. A researcher describes a task or analysis in a chat interface; Claude Science writes and runs the necessary Python, R, or shell code in a sandbox; retrieves data from connected databases; and saves results as versioned artifacts with a full provenance record.

This is meaningfully different from a general-purpose AI assistant in a way that matters for scientific work. A general AI can discuss biology and write code suggestions. Claude Science can execute that code on your local infrastructure, connect to live databases, manage compute environments, orchestrate cluster jobs, and record every step in a retrievable audit trail.

The Agent Architecture

Users interact with a generalist coordinating agent. This agent has access to more than 60 curated skills and connectors pre-configured for scientific domains. It can spin up specialist agents for specific tasks and interact with specialist agents created by the user.

A dedicated reviewer agent runs in parallel. This reviewer inspects outputs as they are produced, flagging incorrect citations, untraceable numbers, and figures that do not match their underlying code. The reviewer self-corrects where possible. Anthropic explicitly notes that the reviewer reduces errors but does not eliminate them, and that results should be verified before use in research, publication, or downstream decisions.

Because agents work inside a running session that holds context in memory, even large datasets only need to be loaded once per session. This is practically significant for genomics and single-cell work where datasets can be very large.

Session Forking

Users can fork a session at any point to compare two analytical approaches without losing the original thread. This is the equivalent of creating a branch in a version control system, allowing researchers to explore alternative methods while preserving the primary workflow.

Data Privacy and Infrastructure

Claude Science runs on the user’s own infrastructure. Large or sensitive datasets never have to leave the systems they are already on. Only the context needed for each step of the analysis is sent to Claude. Claude does not train on user conversations, uploaded files, or research data. For Team and Enterprise accounts, admins can configure data retention policies.

Rich Scientific Artifacts and Provenance

Provenance is the distinguishing architectural commitment of Claude Science, and it is worth understanding precisely what this means.

When Claude Science generates a figure, table, or notebook, the output includes four components: the exact code that generated it, the environment it ran in (dependencies, versions, random seeds where applicable), a plain-language description of what was done, and the full message history that led to the result. This bundle is attached to every artifact.

The practical consequence is that a figure produced in one session can be reproduced, edited, or defended months later by anyone on the team with access to the project. This addresses one of the persistent challenges in computational research: the scenario where a result cannot be reproduced because the exact parameters, package versions, or pipeline steps were not recorded at the time of production.

Built-in Scientific Renderers

Claude Science renders scientific output natively within the application. Supported artifact types include 3D protein structures, genome browser tracks, chemical structure drawings, UMAP plots, dot plots, and other standard scientific visualizations. This eliminates the need to export and open artifacts in separate visualization tools during the analytical workflow.

Figure Iteration in Plain Language

Researchers can request figure edits in plain language: removing gridlines, changing an axis to log scale, adjusting color schemes, or modifying labels. Claude Science interprets the instruction and edits its own underlying code, rerendering the figure. This creates a conversational iteration loop for figure refinement without requiring the researcher to manually edit visualization code.

Manuscript Drafting

Claude Science supports drafting manuscripts within the same environment as the analysis. Figures, tables, and associated code are available in context as the manuscript is drafted, allowing the writing to remain connected to the data and analytical record throughout the process.

Compute Management and HPC Integration

Claude Science manages compute environments automatically. For each analysis, it identifies the required dependencies, sets up the appropriate environment, and handles the job submission to the researcher’s computing resources.

Supported Compute Environments

•         Local laptop or workstation (macOS or Linux)
•         Lab Linux boxes
•         HPC login nodes via SSH, with job submission to Slurm clusters
•         Modal accounts for on-demand cloud compute, scaling from a single GPU to hundreds

The researcher does not need to write the job submission scripts or manage environment configuration for each run. Claude Science handles this process, drafts a plan, asks before reaching new resources, and allows the researcher to review or revoke any decision before the job is submitted.

GPU Scaling

For analyses that require significant compute, including protein folding, large genomics pipelines, or hyperparameter sweeps for machine learning models, Claude Science can scale from a single GPU to hundreds using the researcher’s Modal account or connected HPC. The workbench manages this scaling without requiring the researcher to configure it manually.

Persistent Kernels

Claude Science maintains persistent Python and R kernels across a session. Variables, data, and state loaded into memory at the start of a session remain available throughout without reloading. This is particularly relevant for large datasets where loading is time-consuming and for iterative workflows where state accumulates over many steps.

Scientific Domain Configuration

Claude Science ships pre-configured for major domains in life sciences. This means the relevant tools, packages, and database connectors for each domain are available from the first session without manual setup.

Covered domains include:

•         Genomics
•         Single-cell RNA sequencing
•         Proteomics
•         Structural biology
•         Cheminformatics

When a project spans multiple disciplines, the coordinating agent can engage specialist agents across domains within a single workflow.

Scientific Database Access

Claude Science connects to more than 60 scientific databases. When a researcher asks a question in plain language, specialist agents query and synthesize across the relevant sources. Verified database connections include:

•         UniProt (protein sequences and functional information)
•         PDB (Protein Data Bank: 3D protein structures)
•         Ensembl (genome annotation and comparative genomics)
•         Reactome (biological pathway analysis)
•         ClinVar (genetic variant-disease relationships)
•         ChEMBL (bioactive molecules and drug discovery data)
•         GEO (Gene Expression Omnibus: functional genomics datasets)
•         PubMed and bioRxiv preprints (literature)
•         OpenAlex (open academic citation network)
•         CELLxGENE (single-cell transcriptomics atlas)

Researchers do not need to learn the query language or schema of each database individually. The specialist agents handle this translation.

NVIDIA BioNeMo Integration

Claude Science integrates with NVIDIA’s BioNeMo Agent Toolkit, connecting natively to the life sciences models and libraries in BioNeMo. Verified integrations include:

•         Evo 2 (DNA sequence modeling)
•         Boltz-2 (biomolecular structure prediction)
•         OpenFold3 (protein structure prediction)

Connectors and Extensibility

Claude Science is designed to extend beyond its default configuration. Connectors bring internal APIs, electronic lab notebooks (ELNs), proprietary databases, and bespoke pipelines into the workflow.

Researchers can save any pipeline as a reusable skill. Future sessions automatically inherit saved skills and connectors, meaning the configuration work for a given research program only needs to be done once. This allows labs to build progressively customized environments that reflect their specific workflows and validated tools.

The connector architecture means Claude Science can operate alongside rather than replacing existing lab systems. A lab’s preferred ELN, custom bioinformatics pipeline, or validated internal database can be connected and used within Claude Science rather than replaced by it.

Real-World Beta Use Cases

Three named beta case studies were provided at launch, each verified from Anthropic’s official announcement.

Manifold Bio: Drug Target Nomination

Manifold Bio designs tissue-targeting medicines and tests how millions of candidate binders distribute through living systems. For its latest experiments, Manifold used Claude Science to nominate drug targets. For each tissue and target, Claude Science assessed surface expression, trafficking, and safety, ranking candidates against criteria informed by Manifold’s proprietary internal data. Manifold characterized the key advantage as end-to-end operation: Claude Science gathered the right data and applied appropriate judgment with context built from past programs, without requiring researchers to orchestrate each step manually.

Allen Institute: Multi-Agent Literature Review

Neuroscientist Jerome Lecoq at the Allen Institute used Claude Science to build a multi-agent computational review template comprising approximately 20 custom skills for writing long-form scientific reviews. Sub-agents read through thousands of papers, extracted central claims and key quantitative findings, and stored them in an evidence state database. A pipeline then constructed a narrative arc, writing the review section by section with each section delegated to a specialized sub-agent. Dedicated actor-critic pairs operated within each section: one agent created content while a reviewer agent evaluated it for accuracy and citation fidelity.

Lecoq estimated that this process previously took up to two years for a comprehensive review. His team now has approximately 10 reviews, many exceeding 100 pages, with citations verified by reviewer agents.

UCSF Brain Tumor Center: Molecular Epidemiology

Stephen Francis, associate professor and epidemiologist at the UCSF Brain Tumor Center, used Claude Science to support studies on the molecular epidemiology of glioma. His lab investigates the genetic basis for how thousands of small-effect germline variants combine to shape individual susceptibility. Francis described Claude Science as accelerating comprehensive germline workups across multiple approaches to approximately one-tenth of the previously required time. His group independently validated Claude Science’s results.

Pricing and Access

 

Plan	Monthly Price	Claude Science Access
Free	$0	Not included
Pro	$20/month ($17 annual)	Included in beta
Max 5x	$100/month	Included in beta
Max 20x	$200/month	Included in beta
Team Standard	$30/seat/month ($25 annual)	Admin must enable; Standard seats included
Enterprise	Custom pricing via sales	Included; SSO, SCIM, custom roles, usage analytics

 

Academic and Nonprofit Discount

Anthropic offers a discounted Claude Team plan for active scientific labs at academic institutions and nonprofit research organizations. This plan includes access to Claude Science. Priority is given to biomedical and basic science labs, as well as hard sciences including chemistry, mathematics, computer science, and physics. Eligibility is verified through the lab’s principal investigator. Labs with fewer than 75 people can begin verification directly; larger labs must contact Anthropic sales.

For-profit companies, contract research organizations, and industry research and development teams are not eligible for the academic discount and should use the standard Team or Enterprise plans.

AI for Science Grant Program

Anthropic is supporting up to 50 Claude Science projects with up to $30,000 in credits each. Modal is providing up to $2,000 in additional compute for selected projects. The program targets postdoctoral and graduate research spanning domains and exploring the boundaries of science, with early focus on biology and biomedical research. Applications were open through July 15, 2026, with award notifications by July 31, 2026. Projects run from September 1 to December 1, 2026.

Claude Science vs. Other AI Research Tools

 

Dimension	Claude Science	ChatGPT (with tools)	Google NotebookLM	Gemini Advanced
Primary purpose	Scientific research workbench	General-purpose assistant	Document-grounded Q&A	General-purpose with Google integration
Code execution	Yes, on local infrastructure	Yes, sandboxed	No	Limited
Scientific databases	60+ pre-configured	General web search only	Grounded in user uploads only	Google Scholar via search
Provenance tracking	Built into every artifact	Not built in	Citations only from uploads	Not built in
HPC integration	Yes (Slurm over SSH, Modal)	No	No	No
3D protein rendering	Native	Not native	No	No
Data stays local	Yes	No (sent to OpenAI)	No (sent to Google)	No (sent to Google)
Reviewer agent	Yes, background citation and calculation checking	No	No	No
Persistent kernels	Yes (Python and R)	Session only	No	No
Session forking	Yes	No	No	No
Platform	macOS, Linux (desktop app)	Web, app	Web	Web, app
Current scope	Life sciences, with hard sciences	General	Any domain (upload-dependent)	General

 

Claude Science vs. Traditional Jupyter Workflows

A Jupyter notebook gives a researcher a code execution environment and a way to annotate outputs. Claude Science adds natural language interaction, automatic environment management, database connectivity, compute orchestration, and provenance bundling. The two are not directly comparable: Jupyter is a tool a researcher uses to write and run code; Claude Science is an environment that can manage the full analytical pipeline, with the researcher directing in plain language.

Claude Science acknowledges this lineage explicitly. The official announcement describes it as operating “like a Jupyter Notebook” in terms of access: available locally or on a remote machine. The difference is in what the researcher is responsible for. In Jupyter, the researcher manages everything manually. In Claude Science, the coordinating agent handles environment setup, database querying, compute submission, and provenance recording.

Claude Science vs. ChatGPT

ChatGPT can discuss scientific topics, generate code, and search the web. It cannot connect to specialized scientific databases, run analyses on local infrastructure, submit jobs to an HPC cluster, maintain persistent kernel state, or produce artifacts with a full provenance record. For tasks that require a general-purpose conversation about science or code generation for review, ChatGPT is adequate. For tasks that require executing analyses on real data with reproducible outputs, Claude Science provides infrastructure that ChatGPT’s general-purpose design does not include.

Claude Science vs. NotebookLM

NotebookLM is a document-grounded question-answering tool. It reasons within the documents a user uploads and will not draw on general training knowledge or live databases. It does not execute code, render scientific visualizations, or connect to external databases. NotebookLM is useful for synthesizing a specific corpus of uploaded research papers. Claude Science is for conducting research, running analyses, and producing new results. The two tools address fundamentally different problems.

Who Should Use Claude Science

Well Suited For

•         Computational biologists and bioinformaticians running standard pipelines (RNA-seq, ATAC-seq, proteomics, structural biology)
•         Principal investigators who want to accelerate literature review and synthesis across large paper sets
•         Graduate students and postdocs working on multi-step analyses that require database querying and code execution
•         Research labs that need audit trails for results used in publications or grant applications
•         Labs running analyses on sensitive data that cannot leave institutional systems
•         Multi-disciplinary projects requiring integration across genomics, proteomics, and structural biology in one session
•         Labs with HPC infrastructure that want AI-assisted job submission and environment management

Less Well Suited For

•         Windows users (Claude Science is not available on Windows at launch)
•         Researchers outside life sciences and hard sciences looking for deep domain-specific configuration
•         Labs that need clinical or diagnostic decision support (Claude Science is explicitly not intended for clinical use)
•         Researchers who prefer full manual control over every step of their pipeline without AI involvement
•         Work that requires real-time collaboration between multiple users simultaneously (Claude Science is session-based)

Current Limitations and Beta Considerations

Claude Science is in public beta. Several limitations are known and should be understood before adoption.

•         Windows is not supported. The application runs on macOS and Linux only.
•         The reviewer agent reduces errors but does not eliminate them. Anthropic explicitly states that results should be verified before use in research, publication, or downstream decisions.
•         The reviewer checks claims against the execution record but does not re-run analyses independently. This means it can identify mismatches between stated and actual results, but cannot verify that the analysis itself is scientifically correct.
•         Domain coverage is currently weighted toward life sciences. Researchers in other scientific domains will find less pre-configured infrastructure.
•         Beta features are subject to change. Admins deploying Claude Science for Enterprise teams are advised to review documentation before rollout.
•         Claude can make mistakes in complex multi-step analyses. The long-running nature of some pipelines means errors may compound before the reviewer catches them.
•         Connectivity for intensive HPC work has been noted as an area of ongoing development, with some early users reporting stability issues during long sessions on remote infrastructure.

Privacy and Security Considerations

•         Claude does not train on user conversations, uploaded files, or research data.
•         Code runs in a sandboxed environment. Users approve each new folder access, network host, and remote job before Claude can use it.
•         Data stays on the user’s infrastructure. Only the context needed for each analytical step is sent to Claude.
•         Enterprise accounts include SSO and SCIM provisioning, custom roles, and usage analytics.
•         Enterprise plan includes HIPAA readiness and compliance tooling.
•         Unpublished findings, grant drafts, and proprietary datasets are not used for model training.
•         Team and Enterprise admins can configure data retention policies for their organization.

Key Takeaways

•         Claude Science launched June 30, 2026, as a public beta desktop application for macOS and Linux.
•         It is not a new AI model. It runs on the same Claude models (including Opus 4.8) available on Pro, Max, Team, and Enterprise plans.
•         The application connects to more than 60 scientific databases, manages compute environments including HPC clusters, and produces artifacts with full provenance records.
•         Every output includes the exact code, execution environment, plain-language description, and message history that produced it, enabling reproducibility months later.
•         A reviewer agent checks citations and calculations in the background, flagging and self-correcting errors where possible, but does not eliminate them.
•         Session forking allows researchers to compare analytical approaches without losing the original workflow.
•         Data stays on the researcher’s own infrastructure. Only the context needed for each step is sent to Claude.
•         Academic and nonprofit labs are eligible for a discounted Team plan. Anthropic is also supporting up to 50 AI for Science projects with up to $30,000 in credits.
•         Current limitations include no Windows support, beta-stage stability, and a reviewer that reduces but does not eliminate errors.
•         Claude Science is explicitly not intended for clinical or diagnostic use.

FAQ

Is Claude Science a new AI model?

No. Claude Science is a public beta application that runs on the same Claude models available on existing plans, including Claude Opus 4.8. The application adds scientific tooling, database connections, compute management, and provenance tracking around those models. The models themselves are unchanged.

What can Claude Science do that a general AI assistant cannot?

Claude Science can execute code on the researcher’s own local infrastructure, connect to more than 60 specialized scientific databases, submit and manage jobs on HPC clusters and GPUs, maintain persistent kernel state across a session, produce artifacts with full provenance records, and run a reviewer agent that checks citations and calculations in real time. General AI assistants can discuss science and generate code for review, but cannot execute analyses, connect to live scientific databases, or manage compute environments.

What does provenance mean in Claude Science?

Provenance means that every artifact produced by Claude Science, including figures, tables, and notebooks, includes the exact code that generated it, the environment it ran in (dependencies, versions, and random seeds where applicable), a plain-language description of what was done, and the full message history that led to the result. This record allows any result to be reproduced, edited, or independently verified months after it was produced.

What databases does Claude Science connect to?

Claude Science connects to more than 60 scientific databases. Verified connections include UniProt, PDB, Ensembl, Reactome, ClinVar, ChEMBL, GEO, PubMed, bioRxiv, OpenAlex, and CELLxGENE, among others. Specialist agents query these databases in response to plain-language research questions, translating between the researcher’s intent and each database’s schema and query language.

Where does Claude Science run?

Claude Science is a desktop application that runs on macOS 13 or later (Apple Silicon or Intel) and Linux x64. Analyses run on the researcher’s own infrastructure: laptop, lab Linux box, or HPC login node via SSH. On-demand cloud compute is available through Modal. Data stays on existing systems; only the context needed for each analytical step is sent to Claude.

Is Claude Science available on Windows?

No. Claude Science is available on macOS and Linux only at the time of its June 30, 2026 launch. Windows support has not been announced.

Who can access Claude Science?

Claude Science is in beta for Claude Pro, Max, Team, and Enterprise subscribers. Team and Enterprise members need their organization’s admin to enable Claude Science first. Free plan users do not have access.

Is there a discount for academic labs?

Yes. Anthropic offers a discounted Claude Team plan for active scientific labs at academic institutions and nonprofit research organizations. Priority is given to biomedical, basic science, chemistry, mathematics, computer science, and physics labs. Eligibility is verified through the lab’s principal investigator. Labs with fewer than 75 people can begin verification directly; larger labs should contact Anthropic sales.

Does Claude Science replace specialized tools like Jupyter or R?

No. Claude Science is designed to work alongside existing tools, not replace them. It can connect to existing pipelines, ELNs, and validated tools through connectors. The application is more accurately described as an orchestration environment that coordinates existing tools and adds AI-assisted workflow management, database access, and provenance tracking. Jupyter notebooks remain usable within this workflow.

Is my research data private?

Yes. Claude does not train on user conversations, uploaded files, or research data. Data stays on the researcher’s own infrastructure. Only the context needed for each analytical step is sent to Claude. Enterprise admins can configure data retention policies. Unpublished findings, grant drafts, and proprietary datasets remain private.

Can Claude Science be used for clinical or diagnostic work?

No. Anthropic explicitly states that Claude Science is a research tool and is not intended for clinical or diagnostic use.

How accurate is Claude Science?

Claude Science includes a reviewer agent that checks citations and calculations in the background, flagging errors and self-correcting where possible. Anthropic is explicit that the reviewer reduces but does not eliminate errors, and that results should be verified before use in research, publication, or downstream decisions. In early beta use, the UCSF Brain Tumor Center reported independent validation confirming that Claude Science can produce rapid and robust analyses.

What is the AI for Science program?

Anthropic is supporting up to 50 Claude Science projects with up to $30,000 in credits each. Modal provides up to $2,000 in additional compute for selected projects. The program targets postdoctoral and graduate research with an early focus on biology and biomedical research. Applications closed July 15, 2026; projects run September 1 to December 1, 2026.

Conclusion

Claude Science is a meaningful attempt to solve a real problem in computational research: the fragmentation of tools, databases, and compute resources that forces researchers to spend significant time on infrastructure rather than science.

Its architectural commitments are coherent. Running on the researcher’s own infrastructure addresses data sensitivity concerns that have slowed AI adoption in academic and pharmaceutical research. Built-in provenance tracking addresses reproducibility, one of the most persistent challenges in computational science. The reviewer agent represents an honest acknowledgment that AI systems make errors and that a validation layer is necessary for scientific work.

The beta limitations are also real. Windows users cannot access it. The reviewer does not eliminate errors. Beta stability on long HPC sessions is still being refined. And the current configuration weights heavily toward life sciences, limiting immediate value for researchers in other domains.

The most instructive framing may come from how Anthropic positions it: not as a smarter model, but as a better place to work. For scientists who already use Claude and want to conduct analyses directly inside a structured, reproducible research environment rather than copying outputs into separate tools, Claude Science offers infrastructure that did not previously exist in this form.

Whether it becomes a standard part of scientific workflows will depend on how the beta refines, whether Windows support arrives, and whether the provenance and reproducibility claims hold up under broader use across diverse research programs.

About the Author

I’m Sanwal Zia, an SEO strategist with more than six years of experience helping businesses grow through smart and practical search strategies. I created Optimize With Sanwal to share honest insights, tool breakdowns, and real guidance for anyone looking to improve their digital presence. You can connect with me on YouTube, LinkedIn, Facebook, Instagram, or visit my website to explore more of my work. 

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