Inside Chai Discovery’s rapid rise from OpenAI to Eli Lilly

How Chai Discovery quietly became biotech’s new star

Drug discovery has always been slow, expensive, and filled with uncertainty. Chai Discovery entered this space with a bold idea: use advanced AI models to design better drug molecules from the start.

In just over a year, the startup has become one of the most talked-about names in AI-driven biotech.

According to company announcements, Chai Discovery was founded in 2024 and completed a $70 million financing in August 2025, followed by a $130 million Series B on December 15, 2025, bringing the disclosed total funding to about $225 million and valuing the company at roughly $1.3 billion.

Why drug discovery desperately needs change

Traditional drug discovery often relies on high-throughput screening, a costly trial-and-error process that tests massive numbers of molecules. Success rates are low, timelines stretch for years, and promising ideas frequently fail before reaching patients.

These challenges have pushed researchers to explore new tools. AI offers a way to analyze biological data faster and design molecules more precisely. Chai Discovery is part of this new wave, aiming to replace guesswork with smarter, data-driven design.

Chai’s founding story began at OpenAI

Although Chai Discovery is young, its origins stretch back several years. The founders engaged early with OpenAI leadership and used OpenAI offices during Chai’s early days, and OpenAI later participated as an early investor, according to reporting and company statements.

Joshua Meier previously worked in AI research roles, including at OpenAI and at Facebook AI Research, where he contributed to early transformer protein language model research before moving into industry drug discovery work.

His background in research and engineering helped shape early ideas about applying transformer-based models to biological data and protein design.

Why the idea was initially put on hold

Despite early interest, the founders believed the technology was not ready. AI models capable of handling complex protein structures were still immature, making real-world drug design difficult at the time.

Meier chose to continue building his expertise elsewhere. That decision proved critical, allowing him to contribute to major breakthroughs that later became foundational to Chai’s current technology.

Facebook research shaped Chai’s future models

At Facebook, Meier worked on ESM1, the first transformer-based protein language model. This project showed that protein sequences could be analyzed similarly to human language.

That work became a key precursor to Chai’s approach. It demonstrated how AI could learn biological patterns at scale, opening new doors for protein engineering and drug discovery.

Experience at Absci refined the vision

After Facebook, Meier spent three years at Absci, an AI-driven biotech company focused on drug creation. This role exposed him to real-world pharmaceutical pipelines and industry constraints.

The experience helped clarify what worked and what did not. By the time Chai launched, the founders had a sharper understanding of how AI could fit into practical drug development.

Chai officially launched in 2024

By 2024, Meier and Jack Dent felt the technology had finally caught up to their ambitions. They reached back out to Sam Altman and officially launched Chai Discovery.

The founding team also included Matthew McPartlon and Jacques Boitreaud. Early on, the company operated out of OpenAI’s San Francisco offices, benefiting from close proximity to top AI talent.

OpenAI became an early Chai backer

Reporting and the company press release say OpenAI provided early incubation support, including office access, and participated in Chai’s initial funding rounds.

This backing helped Chai attract additional investors and talent. It positioned the company as a serious player in the fast-growing AI biotech ecosystem.

Chai-2 aims to redesign antibodies

Chai’s core product is its Chai-2 algorithm, designed to develop antibodies. Antibodies play a critical role in fighting disease and are central to many modern therapies.

The company describes its software as a computer-aided design suite for molecules. The goal is to help scientists create better drug candidates faster and with greater precision.

Massive funding fueled rapid expansion

On December 15, 2025, Chai announced a $130 million Series B co-led by Oak HC/FT and General Catalyst, valuing the company at approximately $ 1.3 billion.

The funding round cemented Chai’s status as one of the flashiest startups in AI biotech. It also gave the company resources to scale research and expand partnerships.

Eli Lilly partnership marked a turning point

Chai’s partnership with Eli Lilly was a major milestone. Under the deal, the pharmaceutical giant will use Chai’s software to help develop new medicines. The collaboration validated Chai’s technology in the eyes of the industry.

It also highlighted growing interest among major drugmakers in AI-driven discovery tools. Chai’s announcement came shortly before Eli Lilly revealed a separate partnership with NVIDIA.

That deal involves a billion-dollar AI drug discovery lab in San Francisco. The timing underscored how competitive the space has become. Big pharma and tech companies are racing to gain an edge in AI-powered medicine development.

Backers believe Chai’s models will deliver

General Catalyst and other backers have said they expect Chai’s approach to shorten timelines and improve the rate at which molecules are suitable for clinical development, reflecting investor optimism in the company’s early results.

Supporters argue the advantage is not just speed. They believe AI models like Chai’s could unlock entire classes of medicines that were previously too difficult to develop.

It’s worth checking out Sam Altman’s take on an approaching AI turning point, because it adds a big-picture lens to what’s unfolding now.

What Chai’s rise says about biotech

Chai Discovery’s rapid rise highlights a shift in biotech. AI-first startups are no longer experimental side projects but central players in drug development.

As partnerships deepen and AI models continue to improve, the role of these startups is likely to expand even further. Tools like Chai’s are being positioned earlier in the drug design process, where better decisions can save years of work and enormous costs.

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This slideshow was made with AI assistance and human editing.

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