By Patrick Ip
Legal tech funding is booming, but the money isn’t spreading evenly across the market.
Last year, Crunchbase News reported that legal tech startup investment was riding high as investor enthusiasm for AI reshaped legal software funding, citing a Goldman Sachs report estimating that 44% of legal work could eventually be automated. That concentration has helped create one of the clearer success stories in legal AI — and may also be obscuring an adjacent market that remains far less developed.
Using disclosed funding totals for a selected group of plaintiff-side legal AI companies, the imbalance is hard to miss.
EvenUp has raised $370 million, Eve $164 million, Supio $85 million, and Darrow $63 million, for a combined total of roughly $682 million. Plaintiff-focused companies account for about 71% of disclosed capital for legal AI, suggesting investors have found a part of the sector where adoption, workflow clarity and venture-scale narratives already line up.
That investor interest is not difficult to understand. Plaintiff firms tend to share more standardized workflows around client intake, case evaluation, medical review and demand generation — all areas where AI can automate repetitive work and improve throughput. As those firms have adopted software, the category has become easier to understand, distribute and fund.
The underserved side: legal defense
The defense side, by contrast, remains underdeveloped and may present the next big opportunity.
Corporate legal departments and the law firms managing high-volume defense work still rely heavily on fragmented systems, spreadsheets, email-based coordination and outside counsel processes that were not designed to produce portfolio-wide visibility. For companies facing hundreds or thousands of active matters, litigation is often still run more as a services function than a software-enabled one.
That creates a sizable but harder-to-package opportunity. Retailers, insurers, healthcare systems and financial services companies can each manage large litigation portfolios, yet many still lack a unified view of case risk, settlement patterns, legal spend and outside counsel performance. The need is not new. What has been less clear is whether a venture-backable software category could be built around it.
Part of the reason defense-side legal AI has lagged is structural. Workflows vary widely by industry, matter type and regulatory context, making the market less standardized than plaintiff-side practices. Buying decisions also tend to run through general counsels, legal operations teams and outside counsel relationships, which can lengthen sales cycles and make the category look less immediately viable to investors.
But a shift is underway. Last fall, Crunchbase News reported that legal tech funding reached record highs in 2025, reinforcing how quickly investor attention has shifted toward AI-enabled legal workflows. As plaintiff-side firms get faster at sourcing, valuing and prosecuting claims with software, the operational pressure on defense teams mounts. At the same time, AI is making it more feasible to turn messy litigation workflows into systems that can surface comparable matters, flag risk earlier and benchmark outcomes across portfolios.
From an investor perspective, that makes defense-side litigation AI look less like a niche and more like an underbuilt segment of a broader legal software market. If plaintiff-side investment reflects where legal AI has already become easy to fund, defense-side infrastructure may represent where the next category still has room to form.
Investors, take notice
For venture capitalists, this is the kind of asymmetry worth watching: a large enterprise market with measurable pain points, improving technical feasibility, and no entrenched category leader yet. What investors should watch is whether startups in the category can pair proprietary outcome data with repeatable enterprise adoption — the combination most likely to produce a durable category leader.
One emerging approach on the defense side is exposure and settlement benchmarking: using historical resolution data to estimate settlement ranges, legal spend and case risk across similar matters. In practice, that can mean comparing claims by jurisdiction, plaintiff firm, claim type or other operating variables to help in-house teams make faster and more consistent decisions.
If the category scales, one potential moat may come from proprietary outcome data. Defense-side settlement details, matter economics and resolution patterns are often difficult to reconstruct from public records alone.
A platform that aggregates and normalizes those signals across customers could build a data asset that becomes more useful with scale — a familiar dynamic in vertical software, and a potential early signal for investors of durable advantage in defense-side legal AI.
There is still no clear, scaled, venture-backed winner built specifically around defense-side litigation intelligence. For startup and growth investors, that makes the segment less a settled market than an open question: whether one of legal AI’s next durable companies will emerge not from the workflows that have already attracted the most capital, but from a large enterprise category whose software stack is still taking shape.
Patrick Ip is CEO and co-founder of Theo Ai, which builds AI-powered litigation intelligence for corporate defense teams and law firms.
Related Crunchbase query:
Related reading:
- Legal Tech Startup Investment Is Riding High, Thanks To AI Boost
- EvenUp, AI Software For Personal Injury Law, Doubles Valuation To $2B As Legal Tech Funding Hits Record High
- Highest Count Of New Unicorns Join Crunchbase Board In Over 3 Years As Exits Also Gain Steam
- Wheels Of Justice Slow To Accept Legal Tech As Funding Falls
Illustration: Dom Guzman
