Converge Bio Raises $25M, Backed by Bessemer and Executives From Meta, OpenAI, and Wiz

Artificial intelligence is rapidly reshaping drug discovery as pharmaceutical and biotech companies look to shorten research timelines, reduce costs, and improve success rates. With more than 200 startups now working to embed AI directly into research workflows, investor interest in the sector continues to grow. Converge Bio is the latest company to benefit from this momentum.

The Boston- and Tel Aviv-based startup has raised a $25 million oversubscribed Series A round led by Bessemer Venture Partners. TLV Partners, Saras Capital, and Vintage Investment Partners also participated, with additional backing from executives affiliated with Meta, OpenAI, and Wiz.

Converge Bio uses generative AI trained on molecular data to help pharmaceutical and biotech companies accelerate drug development. In practice, the company trains models on DNA, RNA, and protein sequences and integrates them directly into existing research workflows.

“The drug-development lifecycle has defined stages — from target identification and discovery to manufacturing, clinical trials, and beyond — and within each, there are experiments we can support,” said Dov Gertz, CEO and co-founder of Converge Bio. He added that the platform continues to expand across these stages to help bring new drugs to market faster.

The startup has already launched customer-facing systems and currently offers three leading AI solutions: one focused on antibody design, another on protein yield optimization, and a third on biomarker and target discovery.

Using the antibody design system as an example, Gertz explained that it combines multiple components into a single workflow. A generative model creates novel antibodies, predictive models evaluate them based on molecular properties, and a physics-based docking system simulates three-dimensional interactions between antibodies and their targets. According to Gertz, the value lies in the complete system rather than in any single model, enabling customers to use ready-to-deploy tools without assembling complex pipelines.

The Series A funding comes roughly a year and a half after Converge Bio raised a $5.5 million seed round in 2024. Since then, the two-year-old company has scaled rapidly, completing more than 40 programs with over a dozen pharmaceutical and biotech customers. Its clients span the U.S., Canada, Europe, and Israel, with expansion into Asia now underway.

The team has grown to 34 employees, up from nine in November 2024. Converge has also begun publishing case studies, including one in which it helped a partner increase protein yield by 4 to 4.5 times in a single computational iteration, and another where the platform generated antibodies with extremely high binding affinity in the single-nanomolar range.

Image Credits: Converge Bio

Interest in AI-driven drug discovery has surged across the industry. Last year, Eli Lilly partnered with Nvidia to build what they described as the pharmaceutical industry’s most powerful supercomputer for drug discovery. In October 2024, the team behind AlphaFold from Google DeepMind received a Nobel Prize in Chemistry for their work on protein structure prediction.

Gertz said the broader industry momentum reflects a shift away from trial-and-error approaches toward data-driven molecular design. While large language models are attracting attention for their potential in drug discovery, challenges remain with accuracy and validation. To address this, Converge combines generative models with predictive filters to reduce risk before experimental validation.

Gertz also noted that Converge does not rely on text-based models for core scientific understanding. Instead, its systems are trained directly on biological data, including DNA, RNA, proteins, and small molecules. Text-based models are used only as supporting tools, for example, to help navigate scientific literature.

Yann LeCun: I'm not interested in LLMs anymore - they're the past. The future is in four more interesting areas: machines that understand the physical world, persistent memory, reasoning, and planning. pic.twitter.com/qRH7XVlbWq — Victor (@victor_explore) April 12, 2025

“Our vision is that every life-science organization will use Converge Bio as its generative AI lab,” Gertz said. “Wet labs will always exist, but they’ll be paired with generative labs that create hypotheses and molecules computationally. We want to be that generative lab for the entire industry.”

The article has been updated to include information on the number of customers.