Profluent

Today we’re announcing $106M in new funding led by Altimeter Capital and Bezos Expeditions. This brings our total to $150M to scale our frontier AI models which make biology programmable. Our frontier models have generated functional proteins (Nature Biotech, 2023), created the first CRISPR system designed from scratch (Nature, 2025), and showed clear scaling behavior (NeurIPS spotlight, 2025). The opportunities ahead are unimaginable. If you’re excited by shaping the future of biology – join us in pushing the science forward. Forbes: forbes.com/sites/amyfeldm… Press Release: businesswire.com/news/home/2025… -- Nature Biotech, 2023: nature.com/articles/s4158… NeurIPS spotlight, 2025: biorxiv.org/content/10.110… Nature, 2025: nature.com/articles/s4158…

What do AI-designed proteins look like in the field? 🌾🚜 On Monday, @thisismadani joins @Corteva at @WorldAgriTech to share how Profluent's AI models are engineering proteins for gene editing solutions that address real problems farmers face. March 16 · 12:30pm · San Francisco · World Agri-Tech worldagritechusa.com/agenda-ai-benc…

📄 Read the full paper here: nature.com/articles/s4158… 🧑‍💻 And explore the tool: protein2pam.profluent.bio

We’re excited to share our latest work published today in @NatureBiotech: Protein2PAM, an AI model that enables the rapid design of CRISPR editors with new PAM recognition And we’re making the model freely available for research and commercial use: protein2pam.profluent.bio

Great event at @benchling! We're excited to be among so many great teams creating more and better medicines with AI. Thanks for having us, @sajithw

Our BD team just wrapped a fun year-end off-site (spoiler: we did an escape room!) Now we’re gearing up for the annual trek to JPM next month. If you’d like to connect and learn more about the intersection of AI and protein design—gene editing, antibodies, and beyond—reach out, our DMs are open.

The work will combine Ensoma’s powerful in vivo HSC engineering platform with Profluent’s frontier AI models for protein design to create the next generation of custom-designed editors and intelligent delivery platforms to unlock treatments previously out of reach.

Today we’re excited to announce a new strategic collaboration with @EnsomaBio to advance AI-designed base editors for hematopoietic stem cell (HSC) therapies. The goal: durable, one-time treatments that target the root causes of hematologic and immune diseases. businesswire.com/news/home/2025…

📅  Thu 4 Dec 4:30 - 7:30 PM PST 📍Exhibit Hall C,D,E #1702 🔗 neurips.cc/virtual/2025/l… 👀 Look for Aadyot, lead ML scientist at Profluent!

The upshot is that larger models generate more viable proteins across more protein families, especially those under-represented in the training data. This unlocks design for therapeutic proteins, like ultra-compact gene editors, that were previously out of reach.

#NeurIPS2025 friends! Meet the Profluent team *today* to talk about ProGen3, our generative protein language model that’s solving problems in medicine and agriculture. We're sharing how we built ProGen3 and how we validated it with real wet-lab data.

Or catch us at our spotlight poster on Thursday afternoon to hear the latest on what we're building at Profluent. 📅  Thu 4 Dec 4:30 - 7:30 PM PST 📍Exhibit Hall C,D,E #1702 🔗 neurips.cc/virtual/2025/l…

Drop us a line on this contact form if you'd like to connect with someone from our team in San Diego this week docs.google.com/forms/d/1VYyD_…

Good morning #NeurIPS2025! Profluent is here and we're hiring! Multiple roles across ML science, engineering, SWE, and protein design. job-boards.greenhouse.io/profluent

We have multiple team members on site. If you're interested in chatting, contact us here! docs.google.com/forms/d/e/1FAI…

Excited for #NeurIPS2025! Join us to discuss language models for protein design ranging from ProGen3 (NeurIPS spotlight), E1 (our open-source encoder model), and more!

First, yay Profluent - I really admire what they do and hope they succeed. Second - folks, that's a C2H2 ZFP there. Pavletich and Pabo Science 1991. ❤️ Pardon me while I go all warm and fuzzy here.

Love this take from @nathanbenaich and @airstreetpress. What works in natural language can work in protein engineering too. With E1, reading a sequence alongside its evolutionary neighbors leads to stronger results. E1 outperforms ESM-2, ESM C, and PoET on ProteinGym and CAMEO. We built E1 to be open so the community can test it, stress it, and build on it. Benchmarks are a snapshot. The real story is what scientists and engineers do with it in the wild. 🔗 press.airstreet.com/p/profluent-e1…