Compare the Top AI Science Software that integrates with GitHub as of July 2026

This a list of AI Science software that integrates with GitHub. Use the filters on the left to add additional filters for products that have integrations with GitHub. View the products that work with GitHub in the table below.

What is AI Science Software for GitHub?

AI science software uses artificial intelligence to support and accelerate scientific research, discovery, and analysis across multiple disciplines. It helps researchers analyze complex datasets, run simulations, and uncover patterns that are difficult to detect with traditional methods. The software often supports modeling, hypothesis generation, and experiment optimization using machine learning techniques. Many AI science platforms integrate with research databases, laboratory systems, and high-performance computing environments. By automating analysis and enhancing insight generation, AI science software speeds up innovation and scientific breakthroughs. Compare and read user reviews of the best AI Science software for GitHub currently available using the table below. This list is updated regularly.

  • 1
    OpenAI deep research
    OpenAI's deep research is an AI-powered tool designed to autonomously conduct complex, multi-step research tasks across various domains, such as science, coding, and mathematics. By analyzing user-provided inputs—such as questions, text documents, images, PDFs, or spreadsheets—the system formulates a structured research plan, gathers relevant information, and delivers comprehensive responses within minutes. It also provides process summaries with citations, helping users verify sources. While this tool significantly accelerates research efficiency, it may occasionally produce inaccuracies or struggle to differentiate between authoritative sources and misinformation. Currently available to ChatGPT Pro users, deep research represents a step toward AI-driven knowledge discovery, with ongoing improvements planned for accuracy and response time.
  • 2
    Scispot

    Scispot

    Scispot

    Scispot powers life science labs with a unified LabOS™ platform, combining ELN, LIMS, SDMS, QMS, and AI in one configurable, no-code system. Built for CROs, Molecular Diagnostics, Pathology, Pharma QC, and Drug Discovery, Scispot streamlines sample management, inventory automation, and regulatory compliance. Connect with 200+ lab instruments and thousands of apps to eliminate data silos while maintaining FDA 21 CFR Part 11, GxP, GDPR, and HIPAA compliance. Scispot's AI tools transform experimental data into actionable insights, with flexible workflows that adapt as research evolves—without IT support. Trusted by 1000+ scientists globally, Scispot enables rapid deployment so teams focus on science, not administration. Accelerate discoveries, ensure compliance, and scale operations with a platform purpose-built for modern biotech innovation.
  • 3
    Evo 2

    Evo 2

    Arc Institute

    Evo 2 is a genomic foundation model capable of generalist prediction and design tasks across DNA, RNA, and proteins. It utilizes a frontier deep learning architecture to model biological sequences at single-nucleotide resolution, achieving near-linear scaling of compute and memory relative to context length. Trained with 40 billion parameters and a 1 megabase context length, Evo 2 processes over 9 trillion nucleotides from diverse eukaryotic and prokaryotic genomes. This extensive training enables Evo 2 to perform zero-shot function prediction across multiple biological modalities, including DNA, RNA, and proteins, and to generate novel sequences with plausible genomic architecture. The model's capabilities have been demonstrated in tasks such as designing functional CRISPR systems and predicting disease-causing mutations in human genes. Evo 2 is publicly accessible via Arc's GitHub repository and is integrated into the NVIDIA BioNeMo framework.
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