EvenUp
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Last reviewed
Jun 7, 2026
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v1 · 2,001 words
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EvenUp is a San Francisco legal-technology company that builds legal-AI software for plaintiff-side personal-injury law firms. Its core product converts a claimant's medical records, bills, and case files into a demand package, the document a lawyer sends to an insurer to argue what an injury claim is worth. Founded in 2019, EvenUp grew from a single AI-drafted demand letter into a broader Claims Intelligence Platform and became one of the most heavily funded companies in vertical legal technology, reaching a valuation above 2 billion dollars after a 150 million dollar Series E round in October 2025.
EvenUp sells software that automates the paperwork-heavy parts of a personal-injury practice. In a typical case a person is hurt in a car crash, a slip and fall, or a workplace accident, hires a lawyer on contingency, and waits while the firm assembles medical records, calculates damages, and negotiates with an insurer. EvenUp uses machine learning and large language models to read the underlying documents and draft the demand letter, the medical chronology, and related filings, with human reviewers checking the output before it reaches a client or an opposing party.
The company frames its mission as closing the justice gap and leveling the playing field between individual claimants and the insurers they face, which is the source of the name EvenUp. Plaintiffs' lawyers usually lack the claims data that insurers hold, and roughly 99 percent of injury claims settle privately, so there are few public benchmarks for what a given injury is worth. EvenUp argues that pooling case outcomes and standardizing demand documents helps smaller firms and solo practitioners win larger, faster settlements. The United States sees on the order of 20 million injury victims a year, and EvenUp's investors size the personal-injury legal market at roughly 61 billion dollars.
EvenUp was founded in 2019 in San Francisco by three co-founders: Rami Karabibar, the chief executive; Raymond Mieszaniec, the chief operating officer; and Saam Mashhad, the chief product officer. According to backer Bessemer Venture Partners, the idea grew out of Mieszaniec's childhood experience after his father was hurt in a serious car accident and his immigrant family, pressed by mounting bills and unfamiliar with the legal system, settled for far less than the case was worth. Karabibar came from the mobility sector, including time at Waymo, where he saw the cost and inefficiency of handling injury claims at scale, and Mashhad is a former litigation attorney who had watched case value disappear for lack of the right tools.
The founders set out to build, in the company's words, the first AI legal assistant for personal injury. Early versions leaned on commercially available language models to turn rough medical notes into polished legal prose, paired with proprietary annotation models that extracted injuries and procedures from records. Within roughly two years of its seed financing the company had passed 100 employees and positioned itself as the category leader.
EvenUp's flagship output is the demand package, a settlement demand letter supported by an organized summary of medical treatment, bills, and evidence. The platform ingests medical records, police reports, and invoices, extracts the relevant facts, values the claim against a proprietary database of past verdicts and settlements that Bessemer described as exceeding 250,000 records, and drafts a narrative demand. The underlying AI model, which EvenUp markets as Piai, is trained on hundreds of thousands of injury cases and millions of medical-record pages. The company says new cases flowing through customer workflows continuously enrich that dataset, creating a data advantage that is hard for rivals to copy.
Around its Series D in 2024 the company repositioned the product line as the Claims Intelligence Platform, a suite that spans the case lifecycle rather than just the demand letter. Components include Demands and Express Demands for settlement letters, MedChrons for chronological medical summaries, Case Companion for centralized case materials and drafting, Medical Management, a Settlement Repository of past outcomes, Executive Analytics for firm-level reporting, and Communication Agents, a set of AI agents that handle routine client check-ins. An early product called Litty was paired with a deep integration into the Litify case-management system, and the company has since integrated with practice tools such as Clio. In 2025 EvenUp added a feature called Mirror Mode that adapts drafts to replicate an individual firm's tone, structure, and strategy.
A defining feature of EvenUp is that it is not a pure software product. The company employs a large in-house team of more than 100 legal and medical experts, including lawyers, paralegals, and medical professionals, who review and correct generative AI output before it is delivered. EvenUp presents this hybrid of model plus human review as the source of the accuracy and defensibility that legal work requires.
By its October 2025 Series E, EvenUp reported more than 2,000 US law firms on the platform, including about 20 percent of the 100 largest personal-injury firms. The company said its software had been used on more than 200,000 resolved cases tied to over 10 billion dollars in settlement value, that case volume had nearly doubled in six months to roughly 10,000 cases a week, and that annual recurring revenue was doubling year over year. Fortune reported that EvenUp's largest single customer was on a contract worth about 4 million dollars a year.
Adoption stories have continued into 2026. In February 2026, Legal IT Insider reported that John K. Zaid & Associates, a Houston personal-injury firm with around 180 attorneys and staff, credited EvenUp's platform and Communication Agents with a 30 percent month-over-month increase in demand output and sharply higher settlement offers on certain low-value case types, including one chiropractor-only claim that reached a 30,000 dollar policy limit where similar cases had previously settled below 10,000 dollars. As with most vendor-supplied case studies, those figures come from the firm and the company rather than an independent audit.
EvenUp raised money quickly across five priced rounds, with several led or joined repeatedly by the same investors. SignalFire backed the company at seed stage and led the 2021 Series A. Bessemer Venture Partners led the 2023 Series B, Lightspeed Venture Partners led the 2023 Series C, Bain Capital Ventures led the 2024 Series D that made EvenUp a unicorn, and Bessemer returned to lead the 2025 Series E. The company says it had raised about 385 million dollars in total by October 2025, across what it described as four financing rounds in 24 months, each preempted by investors.
| Round | Date | Amount | Lead investor | Valuation |
|---|---|---|---|---|
| Series A | 2021 | Undisclosed | SignalFire | Not disclosed |
| Series B | June 8, 2023 | $50.5M | Bessemer Venture Partners | about $325M |
| Series C | December 2023 | about $35M | Lightspeed Venture Partners | Not disclosed |
| Series D | October 8, 2024 | $135M | Bain Capital Ventures | over $1B |
| Series E | October 7, 2025 | $150M | Bessemer Venture Partners | over $2B |
| Total raised | through Oct 2025 | about $385M |
The Series B of 50.5 million dollars closed at a 325 million dollar valuation and brought total funding to 65 million dollars, with participation from Bain Capital Ventures, the practice-management company Clio, and angels including Behance founder Scott Belsky and DoorDash executive Gokul Rajaram. The 135 million dollar Series D in October 2024, led by Bain Capital Ventures with Premji Invest, Lightspeed, Bessemer, SignalFire, and B Capital, lifted the valuation past 1 billion dollars and was among the largest legal-AI rounds to that point. The 150 million dollar Series E in October 2025 more than doubled the valuation to over 2 billion dollars in less than a year and added REV, the venture arm of RELX, the parent of LexisNexis, as a strategic backer alongside B Capital, SignalFire, Adams Street, HarbourVest, Lightspeed, Broadlight Capital, and Bain.
EvenUp is one of the clearest examples of vertical legal AI, software aimed at a single practice area rather than at lawyers in general. Where firms such as Harvey target large corporate firms, EvenUp, Supio, and the a16z-backed Eve compete for the plaintiff's bar, and EvenUp's founders have described the segment as winner-take-most. The category drew record venture funding in 2024 and 2025, and EvenUp's repeat raises, its proprietary outcome dataset, and the entry of a LexisNexis-affiliated investor mark personal-injury work as a proving ground for applied AI in law.
The company has also drawn scrutiny over how much of its work is actually automated and how reliable the AI is. In late 2024, around the time of its Series D, Business Insider reported, based on interviews with former employees, that EvenUp leaned heavily on human labor despite its AI positioning, that some supervisors told staff not to use the AI because it was unreliable, and that workers spent long hours, in some accounts until 3 a.m., manually correcting drafts. Former staff described errors such as missed injuries, fabricated or hallucinated medical conditions, and incorrectly recorded medical visits, mistakes that could reduce a victim's payout if a human reviewer did not catch them. EvenUp has responded by stressing its hybrid model, its team of more than 100 legal and medical experts, and continual model improvement, and the company has said no such errors reached final client-facing documents.
These concerns sit within a broader debate about AI hallucination in legal work. Stanford researchers have documented that general-purpose language models produce false or misleading answers on a large share of specific legal queries, and US courts have sanctioned lawyers who filed briefs containing fabricated, AI-generated case citations. Because a flawed demand letter can understate an injury and depress a settlement, the accuracy of EvenUp's output bears directly on claimants' compensation, which is why the company emphasizes human review as a safeguard rather than presenting its system as fully autonomous. EvenUp's trajectory illustrates both the commercial pull of domain-specific legal AI and the unresolved tension between marketing AI automation and the human oversight that high-stakes legal documents still require.