Problem

Profluent addresses the bottleneck in protein engineering: biology offers an astronomically large design space, while conventional discovery depends on labor-intensive experiments, expensive instruments, and evolutionary trial and error. The resulting process is slow, costly, and constrained by what nature has already produced, making it difficult to create proteins with precisely targeted activity, stability, specificity, size, or manufacturability. The economic opportunity is to reduce the number of wet-lab iterations and lower the cost and barrier to applications in therapeutics, agriculture, research, and biomanufacturing.

The clearest use case is programmable gene editing. Profluent’s OpenCRISPR-1 shows how an AI-designed protein can deliver activity comparable to SpCas9 with higher specificity while being substantially different in sequence. More broadly, the company aims to design customized editors backward from an intended application, potentially enabling gene-editing systems tailored to particular therapeutic, agricultural, or scientific requirements.

Product / Service

Profluent provides an AI-first protein-design platform built around large protein language models. Its ProGen3 foundation models were trained on more than 3.4 billion protein sequences and can generate novel full-length proteins or redesign domains of existing proteins. The models use biological context and laboratory data to optimize for properties such as activity, expression, stability, and binding affinity, allowing the system to move beyond natural protein scaffolds and create de novo molecules.

The delivery model combines molecule and model access with scientific collaboration. Partners can license protein assets, work with Profluent to co-design new proteins, or join an early-access API program; the company also validates designs through wet-lab and industry partnerships. OpenCRISPR-1 is an open-source example of the platform, freely available for ethical research and commercial use, while more customized gene editors, antibodies, enzymes, antigens, and other biologic formats can be developed for specific applications.

Market

Profluent competes in generative AI for protein design, an emerging segment at the intersection of foundation-model software, synthetic biology, biologics discovery, and programmable medicine. Its target markets include therapeutics, diagnostics, gene editing, agriculture, and industrial or biomanufacturing applications. Comparable AI-native platforms include Generate:Biomedicines, EvolutionaryScale, Cradle, and Latent Labs, although their business models and focus areas vary from therapeutic discovery to general protein engineering tools.

Profluent has substantial research and commercial traction rather than looking like a purely pre-revenue research venture. It raised $106 million in November 2025, bringing total funding to $150 million; its OpenCRISPR-1 editor was reported as being used by thousands of commercial operations, academic researchers, and large pharmaceutical companies. The company has also announced collaborations with Corteva, Revvity, Integrated DNA Technologies, Ensoma, and Eli Lilly, and offers licensing and API access. Public sources reviewed do not establish recognized revenue: one database leaves current revenue blank while another gives an unverified estimate, so the strongest evidence of traction is funding, usage, partnerships, and a growing pipeline of AI-designed biological products rather than disclosed sales.