Latent Labs Unveils Web-Based AI Platform to Democratize Protein Design

Latent Labs, a pioneering biotechnology firm, has introduced LatentX, a web-based artificial intelligence (AI) platform designed to revolutionize protein design. This launch comes approximately six months after the company emerged from stealth mode with $50 million in funding.

Advancing Protein Design with AI

LatentX empowers users—including academic institutions, biotech startups, and pharmaceutical companies—to design novel proteins directly through their web browsers using natural language inputs. This capability extends beyond existing biological molecules, enabling the creation of entirely new proteins such as nanobodies and antibodies with precise atomic structures. Such advancements have the potential to accelerate the development of innovative therapeutics.

Dr. Simon Kohl, CEO and founder of Latent Labs, emphasized the platform’s capabilities:

We have computational ways of assessing how good the designs are, he stated, noting that a significant percentage of proteins generated by the model are viable when tested in laboratory settings.

Distinguishing Features of LatentX

Unlike AlphaFold, which predicts the structures of existing proteins, LatentX is designed to generate entirely new protein structures. This distinction positions LatentX as a tool for not only understanding but also innovating within the realm of protein design.

Dr. Kohl elaborated on this difference:

AlphaFold is a model for protein structure prediction. So it allows you to visualize existing structures, but it doesn’t let you generate new proteins, he explained.

Business Model and Accessibility

Latent Labs adopts a unique business model by licensing its AI platform to external organizations, rather than focusing solely on developing proprietary medicines. This approach aims to make advanced protein design tools accessible to a broader range of entities, including those without the resources to develop their own AI infrastructure.

Dr. Kohl highlighted this strategy:

Not every company is in a position to build their own AI models, to have their own AI infrastructure, and to have their own AI teams, he noted.

While LatentX is currently available for free, the company plans to introduce advanced features and capabilities in the future, which may involve associated costs.

Funding and Strategic Partnerships

Latent Labs’ initial funding round was co-led by Radical Ventures and Sofinnova Partners, with participation from notable investors such as Google’s Chief Scientist Jeff Dean, Cohere founder Aidan Gomez, and ElevenLabs founder Mati Staniszewski. ([latentlabs.com](https://www.latentlabs.com/press-release/latent-labs-secures-50m-in-funding/?utm_source=openai))

In May 2025, the company announced a multi-year collaboration with Amazon Web Services (AWS) to scale its generative AI capabilities for the life sciences sector. This partnership aims to provide biologists, pharmaceutical companies, and biotech innovators worldwide with direct access to AI tools, furthering Latent Labs’ mission to make biology programmable. ([latentlabs.com](https://www.latentlabs.com/press-release/latent-labs-and-aws-announce-collaboration-to-scale-generative-ai-for-the-life-sciences/?utm_source=openai))

Implications for the Biotech Industry

The introduction of LatentX signifies a significant advancement in the field of computational biology. By enabling the design of novel proteins through a user-friendly web interface, Latent Labs is lowering the barriers to entry for protein engineering. This democratization has the potential to accelerate drug discovery processes, enhance the development of personalized medicine, and address previously challenging therapeutic targets.

As the biotech industry continues to integrate AI into its workflows, platforms like LatentX exemplify the transformative potential of combining computational power with biological research. By providing accessible tools for protein design, Latent Labs is contributing to a future where the creation of new therapeutics is more efficient, precise, and widely attainable.