aid: profluent-bio
name: Profluent
description: >-
  Profluent is a Berkeley, California AI biology company building frontier
  protein language models and using them to design functional proteins for
  therapeutics, gene editing, agriculture, and industrial enzymes. Founded by
  Ali Madani — previously architect of the ProGen large language model for
  proteins at Salesforce AI Research — Profluent pairs in-house foundation
  models with a wet lab to author novel proteins from scratch and validate
  them experimentally. The company's research has been published in Nature
  Biotechnology and Nature, and it is best known for OpenCRISPR-1, which it
  describes as the world's first AI-designed gene editor, released freely
  for research and commercial use. Profluent also publishes the ProGen3
  family of protein generation models, ProseLM for structure-conditioned
  protein design, the E1 family of protein encoder models, Protein2PAM for
  CRISPR-Cas PAM specificity prediction, and the CRISPR-Cas Atlas dataset.
  Commercial partnerships include a multi-target collaboration with Eli
  Lilly worth up to $2.25 billion, and deals with Ensoma, Corteva, Integrated
  DNA Technologies, and the Rett Syndrome Research Trust. Profluent is
  backed by Spark Capital, Insight Partners, Air Street Capital, Altimeter,
  and Bezos Expeditions. The company does not publish a hosted developer
  REST API or commercial SDK; its surface area for external builders is the
  Profluent-AI GitHub organization (model weights and inference code), the
  Protein2PAM web tool, and partnership engagements.
type: Index
position: Provider
access: 3rd-Party
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/apis-json-logo.jpg
tags:
  - Artificial Intelligence
  - Protein Design
  - Protein Language Models
  - Foundation Models
  - Generative Biology
  - Gene Editing
  - CRISPR
  - OpenCRISPR
  - ProGen
  - ProseLM
  - Bioinformatics
  - Therapeutics
  - Agriculture
  - Industrial Enzymes
  - Open Source Models
url: https://raw.githubusercontent.com/api-evangelist/profluent-bio/refs/heads/main/apis.yml
created: '2026-05-24'
modified: '2026-05-24'
specificationVersion: '0.20'
apis: []
common:
  - type: DomainSecurity
    url: security/profluent-bio-domain-security.yml
  - type: Website
    url: https://www.profluent.bio
  - type: Platform
    url: https://www.profluent.bio/platform
  - type: Applications
    url: https://www.profluent.bio/applications
  - type: Partnerships
    url: https://www.profluent.bio/partnerships
  - type: Team
    url: https://www.profluent.bio/team
  - type: Newsroom
    url: https://www.profluent.bio/media
  - type: OpenCRISPR
    url: https://www.profluent.bio/modality/opencrispr
  - type: Sandbox
    url: https://protein2pam.profluent.bio
  - type: GitHubOrganization
    url: https://github.com/Profluent-AI
  - type: SourceCode
    url: https://github.com/Profluent-AI/OpenCRISPR
    name: OpenCRISPR
  - type: SourceCode
    url: https://github.com/Profluent-AI/progen3
    name: ProGen3
  - type: SourceCode
    url: https://github.com/Profluent-AI/proseLM-public
    name: ProseLM
  - type: SourceCode
    url: https://github.com/Profluent-AI/E1
    name: E1 Protein Encoder Models
  - type: SourceCode
    url: https://github.com/Profluent-AI/Protein2PAM
    name: Protein2PAM
  - type: SourceCode
    url: https://github.com/Profluent-AI/CRISPR-Cas-Atlas
    name: CRISPR-Cas Atlas
  - type: Publication
    url: https://www.nature.com/articles/s41586-025-09298-z
    name: Design of highly functional genome editors by modelling CRISPR-Cas sequences (Nature, 2025)
  - type: Publication
    url: https://www.nature.com/articles/s41587-024-02123-4
    name: Designing Proteins with Language Models (Nature Biotechnology, 2024)
  - type: Publication
    url: https://www.nature.com/articles/s41587-022-01618-2
    name: Large Language Models Generate Functional Protein Sequences Across Diverse Families (Nature Biotechnology, 2023)
  - type: Publication
    url: https://www.biorxiv.org/content/10.1101/2025.04.15.649055v2
    name: Scaling Unlocks Broader Generation and Deeper Functional Understanding of Proteins (bioRxiv)
  - type: Careers
    url: https://job-boards.greenhouse.io/profluent
  - type: Email
    url: mailto:info@profluent.bio
  - type: Partnerships
    url: mailto:partnerships@profluent.bio
  - type: LinkedIn
    url: https://www.linkedin.com/company/profluent-bio
  - type: Twitter
    url: https://x.com/ProfluentBio
  - type: YouTube
    url: https://www.youtube.com/@Profluent-Bio
  - type: PrivacyPolicy
    url: https://www.profluent.bio/privacy
  - type: TermsOfService
    url: https://www.profluent.bio/terms
  - type: Blog
    url: https://www.profluent.bio/media
maintainers:
  - FN: Kin Lane
    email: kin@apievangelist.com