AI protein design funding tracker (84 deals)

Our funding tracker covering the AI protein design market

Below is the table listing all the deals. You may find our methodology at the end of this page.

And, if you want to gain a deeper understanding of the market and its current dynamics, get our report covering the AI protein design market.

Is AI protein design really a multibillion-dollar market now?

AI protein design has attracted at least $2.75 billion in venture funding, but most startups in the sector are raising far less money than that headline might suggest.

Between January 2024 and September 2026, we identified 84 financing transactions involving 67 companies. The average disclosed round was $36.73 million, while the median was only $15 million. A handful of very large investments explain much of that gap.

Chai Discovery raised $400 million in a single financing, Syneron Bio secured $150 million, and Outpace Bio completed a $144 million Series B. Those deals demonstrate how much investors are willing to commit to promising protein-design technologies, particularly when they have pharmaceutical applications.

But the wider market looks rather different. Nearly half of all recorded transactions were below $20 million, and only eight reached $100 million or more.

The $2.75 billion total is also a minimum because nine transactions have no usable disclosed amount. Several other deals were reported as lower bounds, while some included capital commitments that may not have been fully drawn.

For now, AI protein design looks like a market with a fairly broad group of funded startups and a much smaller set of companies attracting exceptionally large checks.

How many AI protein design startups are actually getting funded?

We found 67 funded AI protein design companies, and 55 of them raised money only once during the period we studied.

That means 82.1% of companies have a single recorded transaction. Another eight businesses completed two financings, while four appeared in three or more deals.

This is worth separating from the total number of transactions. Chai Discovery and Aureka Biotechnologies each recorded three rounds, while Profluent and BigHat Biosciences also appeared more than once.

A company with only one financing in our research may already have raised money before January 2024. It might also have secured enough capital to finance several years of research.

Outpace Bio, for instance, received $144 million in one transaction. EvolutionaryScale raised more than $142 million at Seed. Neither company would necessarily need another round shortly afterward.

Looking at the 67 distinct companies gives us a better idea of how many businesses investors are actually supporting, while the repeated financings show where additional capital is accumulating.

Are a few AI protein design startups taking most of the money?

Funding in AI protein design is extremely concentrated, with the ten largest recipients collecting 63% of all recorded capital.

Chai Discovery leads by a considerable margin. Its three financings total $600 million, almost four times the $158.2 million raised by second-place Aureka Biotechnologies.

Syneron Bio follows with $150 million, ahead of Outpace Bio at $144 million and EvolutionaryScale at more than $142 million.

The top five companies together received 43.4% of the market's disclosed funding.

Meanwhile, 19 companies have no more than $5 million in observable cumulative capital. That group includes businesses whose actual totals may be higher because some financing amounts were undisclosed.

What's striking is how quickly the scale changes. A company can be among the ten largest funding recipients with $75 million, yet Chai alone has raised eight times that amount during the same period.

Which AI protein design companies raised the most money?

Company	Recorded deals	Capital raised
Chai Discovery	3	$600.0M
Aureka Biotechnologies	3	$158.2M
Syneron Bio	1	$150.0M
Outpace Bio	1	$144.0M
EvolutionaryScale	1	≥$142.0M
Profluent	2	$141.0M
Diagonal Therapeutics	1	$128.0M
BigHat Biosciences	2	$119.0M
Peptilogics	1	$78.0M
Infinimmune	1	$75.0M

Is Chai Discovery making the AI protein design market look bigger than it really is?

Chai Discovery accounts for 21.8% of all recorded AI protein design funding, making it by far the biggest influence on the market's headline numbers.

Its largest financing came on July 14, 2026, when the company announced a $400 million Series C at a $3.8 billion valuation. That round alone represents 14.5% of the sector's disclosed capital.

The funding followed Chai's development of AI models for molecular design and a series of relationships with major pharmaceutical companies.

Its commercial activity is increasingly relevant to the investment case. In June 2026, Chai announced a license agreement with Pfizer involving its Chai-3 model. The company also expanded its work with Eli Lilly and announced collaborations involving Novartis, argenx and Bristol Myers Squibb during the summer.

Investors are effectively backing a company that wants its molecular-design software used across numerous drug-discovery programs.

But we should also look beyond Chai. Removing its entire $600 million leaves roughly $2.15 billion in disclosed funding across the remaining businesses.

There is serious financing activity elsewhere, even if Chai has become the standout fundraising success.

What does a normal AI protein design startup actually raise?

The typical disclosed AI protein design round is $15 million, although the amount a startup can realistically target depends heavily on its development stage and business model.

Sixteen financings were below $5 million, while 25 fell between $5 million and $20 million. Those smaller transactions account for 41 of the 84 deals we recorded.

At the other extreme, eight financings reached $100 million or more and together contributed $1.3 billion. That's nearly half of all calculable capital from fewer than one in ten transactions.

An early enzyme-design company looking for several million dollars is operating within a fairly common funding range. A startup seeking $100 million for an AI protein platform is approaching a much narrower group of investors and competing with companies that have already convinced backers to finance ambitious scientific programs.

The stage of development makes the difference more obvious. Median Seed financing stands at $6 million, compared with $19.65 million at Series A and $66.5 million at Series B.

We would use those stage-specific figures before treating the overall market average as a realistic fundraising target.

How much money do AI protein design companies raise per round?

Round size	Deals	Share of deals	Recorded capital
Under $5M	16	19.0%	$40.02M
$5M–under $20M	25	29.8%	$270.00M
$20M–under $50M	18	21.4%	$613.70M
$50M–under $100M	8	9.5%	$531.00M
$100M+	8	9.5%	$1,300.00M
Undisclosed	9	10.7%	Unknown

Which part of AI protein design is getting the most funding?

Antibody and binder design is currently the biggest destination for AI protein design funding, attracting approximately $1.28 billion across 23 transactions.

That category accounts for 46.6% of disclosed capital, despite representing only 27.4% of deals. The difference is considerable.

Research and synthetic-biology protein design comes next with at least $477 million, followed by therapeutic proteins at $435.3 million and peptides at $386.55 million.

The order changes when we compare round sizes. Research and synthetic biology has a median disclosed financing of $35 million, slightly above the $32 million median in antibody and binder design. Both stand well above enzyme and industrial protein engineering.

Several different businesses sit behind these figures. Chai Discovery develops molecular-design models for pharmaceutical partners. Latent Labs builds generative protein-design technology that researchers can use to create and optimize biological molecules. Outpace Bio uses designed proteins in engineered immune-cell therapies.

Investors are financing everything from research tools to drug candidates, but pharmaceutical applications are where the biggest checks are most visible.

Where is the money going within AI protein design?

Category	Deals	Companies	Recorded capital	Median deal
Antibody & Binder	23	16	$1,282.7M	$32.0M
Research & Synthetic Biology	16	11	≥$477.0M	$35.0M
Therapeutic Protein	16	12	$435.3M	$12.7M
Peptide	12	12	$386.55M	$15.5M
Enzyme	10	10	$90.79M	$6.05M
Industrial Protein	6	5	$71.11M	$5.85M
Vaccine & Antigen	1	1	$11.3M	$11.3M

Why are investors spending so much on AI-designed antibodies?

Investors are making especially large bets on AI antibody design because successful platforms could help pharmaceutical companies discover and improve drugs across many different programs.

Chai Discovery gives us a good example. The company develops computational tools that help researchers design molecules and predict how they interact with biological targets.

Its agreements with Pfizer, Eli Lilly and Novartis show the kind of customers these platforms can attract. Instead of developing every drug itself, a molecular-design company can potentially work across several pharmaceutical pipelines.

Diagonal Therapeutics illustrates another approach. In April 2024, the company launched with $128 million to develop agonist antibodies, using computational and experimental techniques to target diseases involving disrupted biological signaling.

BigHat Biosciences combines machine learning and laboratory automation to design therapeutic antibodies. Its Milliner platform integrates computational work with experimental testing, connecting molecular design to drug development.

Better antibody design could save pharmaceutical companies time, improve candidates and make difficult biological targets more accessible.

Of course, the financing figures don't prove that every platform will deliver those results. But the large rounds, growing commercial relationships and investment from established drugmakers give us concrete reasons for the category's popularity.

Why would investors put more than $100 million into an AI protein design seed round?

Some AI protein design startups can raise enormous seed rounds because investors are financing the development of foundational biological AI models, which can require substantial resources from the beginning.

EvolutionaryScale is the clearest example. In June 2024, it announced seed funding exceeding $142 million while introducing ESM3, a generative model capable of designing proteins.

The round was led by investors including Nat Friedman, Daniel Gross and Lux Capital, with participation from Amazon and NVentures, Nvidia's venture investment arm.

ESM3 was developed to work with protein sequences, structures and functions. The potential applications extend from pharmaceutical research to new materials and other biological technologies.

Building this kind of technology requires specialized AI researchers, significant computing resources and experimental work to determine whether generated proteins behave as intended.

EvolutionaryScale was therefore raising money for a broad scientific research platform with ambitions extending across several industries.

In ordinary startup terminology, a seed round suggests a relatively small investment in an early business. EvolutionaryScale shows why that assumption can be misleading in scientific AI.

Are AI protein design startups building software or developing actual drugs?

AI protein design funding covers both software-like research platforms and companies developing physical therapies, with very different costs attached to each business.

EvolutionaryScale is focused on foundational models that scientists can use to generate and study proteins. Latent Labs takes a related approach, building tools that let researchers design molecules such as antibodies and enzymes.

Latent Labs launched publicly in February 2025 with $50 million in total funding, including a $40 million Series A. Its platform aims to make generative protein design accessible to pharmaceutical and biotechnology researchers.

Outpace Bio sits much closer to clinical development. Its August 2024 Series B raised $144 million to advance programmed T-cell therapies toward early clinical proof-of-concept in solid tumors.

Diagonal Therapeutics is another example of capital supporting a specific therapeutic pipeline. Its $128 million financing was intended partly to advance treatments for hereditary hemorrhagic telangiectasia, a rare bleeding disorder.

Clinical programs need manufacturing, testing, regulatory preparation and human trials. Those activities can absorb substantial amounts of money long after the underlying protein-design work has produced a promising candidate.

That's why we need to be careful with the market's aggregate funding figure. A dollar raised for training molecular models and a dollar raised for developing a treatment can support very different activities.

Why are industrial protein and enzyme startups raising smaller rounds?

Industrial protein and enzyme-design companies are raising much smaller venture rounds than their pharmaceutical counterparts, with no financing above $50 million recorded in either category.

The combined capital for both segments is approximately $162 million, spread across 16 transactions.

Epoch Biodesign offers a useful example of the industrial approach. The company uses AI and enzyme engineering to break down difficult-to-recycle materials, including plastics and textiles, into reusable chemical building blocks.

Its technology has to work in industrial processes where cost, material recovery and production efficiency determine whether customers will adopt it.

Resurrect Bio applies computational protein engineering to agricultural disease resistance. Its 2026 Series A reached $10.3 million after an initial close of $8.1 million, with strategic involvement from Corteva Agriscience.

These are practical biological-engineering businesses, but their commercialization paths differ from those of antibody drug developers.

They may grow through corporate partnerships, licensing, manufacturing relationships or strategic funding arrangements that are less visible in a database of venture financings.

What we can establish is that investors are writing smaller observable equity checks for these applications. Whether industrial protein design ultimately becomes a larger commercial market is a separate question.

How far have AI protein design startups actually progressed?

AI protein design remains heavily concentrated at Seed and Series A, although the companies reaching Series B are already raising much larger amounts of money.

We counted 32 Seed financings, 31 Series A rounds, 14 Series B transactions and four Series C deals. Three additional financings had no reliable stage classification.

The typical round grows considerably as companies advance. Median financing increases from $6 million at Seed to $19.65 million at Series A, before reaching $66.5 million at Series B.

A company raising Series B in this market is generally seeking several times more capital than a typical Series A business.

The founding dates suggest the market is still young. Forty-three of the 67 funded companies were established in 2021 or later.

Even so, the largest financings are already supporting companies with substantial research operations, pharmaceutical programs and more demanding development plans.

We see plenty of early-stage activity and a smaller population receiving major follow-on investment. The challenge is how many of those businesses will progress to the next level.

How does AI protein design funding change by stage?

Stage	Deals	Recorded capital	Median deal
Seed	32	$331.81M	$6.0M
Series A	31	$797.90M	$19.65M
Series B	14	$1,037.01M	$66.5M
Series C	4	$535.00M	$60.0M
Unknown	3	$53.00M	$26.5M

Why are so few AI protein design companies reaching Series C?

Series C funding is still rare in AI protein design, with only four recorded transactions compared with 31 Series A financings.

There is a noticeable narrowing earlier in the funding ladder. Series B appears 14 times, less than half the Series A count.

The four Series C deals together represent $535 million, with Chai Discovery responsible for $400 million. That leaves only $135 million in recorded Series C financing across the other three transactions.

These numbers don't prove that startups are failing between stages. The companies raising Series A during this period haven't necessarily had enough time to reach Series B or C, while others may have raised earlier rounds before our observation window began.

Still, the shortage of later-stage transactions deserves attention.

Protein-design businesses often need years to validate their technology, build commercial relationships or demonstrate therapeutic progress. Investors considering a large Series C may also want stronger evidence of revenue, pharmaceutical partnerships or clinical results than was required during earlier rounds.

For now, the market has produced several companies capable of raising nine-figure Series B financings, but relatively few have reached a similarly well-funded Series C stage.

How old are AI protein design startups when they raise big money?

AI protein design startups are receiving large investments surprisingly early, with a median company age of just three years among rounds above $50 million.

Across the full financing population, the median age at fundraising is also three years.

There is a fairly normal progression by stage. Companies raising Seed are typically around two years old, compared with four years at Series A, 5.5 years at Series B and 6.5 years at Series C.

But some companies move much faster.

EvolutionaryScale raised more than $142 million shortly after its formation. Chai Discovery also reached a very large Series C financing within a relatively short corporate history.

Those examples suggest that investors are prepared to back exceptional AI and biological research teams without waiting for a decade of operating history.

The distinction is particularly relevant for foundational-model companies. Their value can depend heavily on technical capability, model performance, intellectual property and access to commercially important biological applications.

Young companies are not automatically receiving small checks in this sector.

Are investors backing new AI protein design startups or mostly funding companies they already know?

Most AI protein design funding is going to businesses that have raised external capital before, with follow-on financings accounting for 81% of recorded deals.

We classified 68 transactions as follow-ons and 16 as first financings. Those follow-on rounds represent approximately $2.40 billion, or 87% of disclosed funding.

The market continues to fund new entrants, but established startups are receiving most of the money.

There is also a distinction between historical follow-on financing and repeated fundraising during our observation window. A company may appear only once between 2024 and 2026 while still having several earlier rounds behind it.

BigHat Biosciences and Outpace Bio, for example, had already secured financing before the period we analyzed. Their later transactions build on existing company histories.

The large follow-on share suggests investors are increasingly financing continued research, therapeutic development and expansion rather than simply paying for the initial creation of new businesses.

Which investors are most active in AI protein design?

AI protein design has no single venture firm dominating the lead-investor market, although a small group of specialist investors appears repeatedly.

We identified 102 distinct lead or co-lead names across the available financing records. Only nine appeared on more than one transaction.

Playground Global led or co-led three rounds with a combined financing value of $91.5 million. Sofinnova Partners appeared twice across rounds totaling $78 million, while Radical Ventures participated as a lead in two transactions totaling $66 million.

Versant Ventures and DCVC Bio also recur, including through Fable Therapeutics' financing history.

But the number of appearances needs some interpretation. D3 LLC and DEEPCORE recur through successive financings involving RevolKa, rather than investments across several unrelated businesses.

At the upper end of the market, large generalist venture investors can become important. Chai Discovery's $400 million Series C brought together Index Ventures, Kleiner Perkins, Sequoia Capital and Dimension.

Specialist biotechnology funds, established venture firms and technology-oriented investors all participate, often depending on whether the company is developing drug candidates, biological foundation models or industrial applications.

Are pharmaceutical giants investing in AI protein design themselves?

Pharmaceutical and technology companies are already involved in a substantial share of AI protein design financings, with strategic investors identified in one-third of recorded transactions.

Across the 84 deals, 28 involved strategic participation. Those transactions had a median round size of $21 million, compared with $13 million for deals without a disclosed strategic investor.

Among the recognizable corporate participants are investment entities associated with AstraZeneca, Pfizer, Merck, Eli Lilly, Regeneron and Bayer.

Their interests are commercially understandable. Better protein-design technology could help drugmakers discover antibodies, improve therapeutic candidates, pursue difficult targets and reduce some of the experimental work involved in early discovery.

Technology companies have a different reason to pay attention. Amazon and NVentures backed EvolutionaryScale, whose protein foundation models require the type of AI computing infrastructure these businesses already support.

Corporate involvement also reaches agriculture. Corteva's participation in Resurrect Bio reflects interest in engineered biological traits that could protect crops against disease.

The presence of strategic investors doesn't guarantee future commercial success, and the total amount contributed by those investors is not always disclosed. Still, their participation shows that established companies are willing to commit capital to protein-design technologies with potential uses in existing industries.

Is the United States taking most of the AI protein design investment?

The United States is comfortably ahead in observable AI protein design funding, accounting for roughly $2.11 billion across 40 recorded deals.

North America as a whole contributes 42 transactions and approximately $2.12 billion. That's 77.1% of all disclosed capital, despite representing only half the deal count.

Europe follows with 20 transactions and $338.65 million. The United Kingdom is its largest identifiable contributor, with 12 deals totaling approximately $219 million.

Asia-Pacific records 18 transactions and at least $247.66 million. China accounts for 11 of those deals, with at least $192.8 million in numerically reported funding.

But China's position is less precisely measured. Several Chinese financings were disclosed through broad RMB ranges rather than exact amounts, making the region's reported dollar total less reliable.

There is also an enormous difference in typical financing size. North America's median disclosed round is $35 million, compared with $6.9 million in Europe and $9.95 million in Asia-Pacific.

The United States clearly leads when it comes to the large, publicly disclosed financings that dominate the sector's capital totals. Other regions have meaningful startup activity, but far fewer recorded nine-figure rounds.

Is AI protein design funding growing steadily, or does it come in waves?

AI protein design funding arrives in bursts, with a handful of large transactions causing much bigger swings in monthly capital than changes in the number of deals.

Across the 32 completed months from January 2024 through August 2026, the market averaged roughly 2.6 transactions per month. The busiest months were October 2024 and November 2025, with six deals each.

Yet July 2026 attracted far more money than either month, reaching $417.16 million across five financings.

Almost all of that amount came from Chai Discovery's $400 million Series C.

March 2026 was another particularly large month, recording $249.3 million across five transactions. November 2025 brought $189.5 million across six deals, including Profluent's $106 million financing.

The difference between an ordinary month and an exceptional one can come down to a single company announcing a major financing.

We also found cases where announcement dates differed from closing dates. Ukko's $45 million financing, for example, closed in 2025 but became public in January 2026.

The market has demonstrated an ability to attract very large rounds, although the timing is irregular and individual announcements can dominate the statistics.

What's still missing from the AI protein design market?

AI protein design has plenty of early funding and several spectacular rounds, but we still have limited evidence of a broad population of companies reaching commercial scale.

The later-stage gap is the first concern. Only four Series C transactions appear in the period, and one company accounts for most of their capital.

Industrial applications also remain relatively small in the available equity data. Enzyme and industrial protein companies have 16 financings between them, but neither category records a round above $50 million.

Vaccine and antigen design is even less represented, with only one qualifying financing. That gives us too little evidence to judge investor demand for the category as a whole.

The bigger question concerns what happens after funding.

AI protein-design companies are pursuing very different outcomes. Some want pharmaceutical partners to use their models. Others aim to develop approved therapeutics, while industrial businesses must prove they can manufacture products at an economically competitive cost.

The financing data gives us evidence of investor interest, but it doesn't establish whether those companies are generating substantial revenue, producing successful clinical results or operating profitable industrial processes.

That is where the next meaningful separation between the strongest companies and the rest of the market is likely to appear.

What should we actually take away from the funding data?

AI protein design has become a serious venture-backed biotechnology market, but investors are clearly much more selective with their largest checks than the headline funding total suggests.

The first conclusion concerns concentration. Sixty-seven companies received investment, yet a small group accounts for most of the money. Chai Discovery is the standout, although several other companies have secured nine-figure financings.

The second is that ordinary fundraising remains much smaller than the biggest announcements imply. The typical disclosed deal is $15 million, and almost half of all recorded transactions fall below $20 million.

Third, pharmaceutical applications are receiving the strongest financial backing. Antibody design leads the market, while therapeutic proteins, peptides and broader biological research platforms also attract substantial amounts. Industrial protein and enzyme engineering remain considerably smaller in the venture data.

Fourth, the market is still relatively young. Most deals are at Seed or Series A, and the number of financings drops sharply at Series B and C. Companies that reach those later stages can raise substantial capital, but relatively few have done so.

Fifth, established investors and corporate backers are playing a meaningful role. Follow-on rounds dominate financing activity, and strategic investors participate in one-third of transactions. Drugmakers and technology companies clearly see potential commercial value in the field.

Finally, AI protein design's biggest unanswered question is whether its best-funded companies can turn advanced computational biology into durable businesses. The sector has demonstrated that investors are willing to spend billions supporting the technology. We still need to see how widely that investment translates into valuable medicines, scalable industrial products and sustainable commercial revenue.