Frameworks, core principles and top case studies for SaaS pricing, learnt and refined over 28+ years of SaaS-monetization experience.
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If Harvey represents agentic AI applied to the rarefied world of Big Law, EvenUp represents something rawer, more visceral. In many ways more consequential: an AI agent that fights for people who have been injured. EvenUp was founded in 2019 by Rami Karabibar, Raymond Mieszaniec, and Saam Mashhad, a team whose backgrounds converge on the specific problem they set out to solve. Karabibar had worked at Waymo, where he witnessed firsthand the operational chaos of managing injury claims at scale. Mieszaniec experienced the impact of a life-changing accident in his own family. Mashhad was a practicing attorney who knew from his own caseload how much value was being lost because personal injury lawyers were drowning in paperwork.
Personal injury law in the United States is a $61 billion industry that operates on a model most people outside the legal profession don’t understand. When someone is injured, in a car accident, a slip and fall, a medical malpractice incident, they typically hire an attorney on a contingency basis. The attorney takes no fee upfront and receives a percentage (usually 33 to 40 percent) of whatever settlement or verdict is eventually recovered. The attorney’s job is to build the strongest possible case, quantify the damages, and either negotiate a settlement with the insurance company or take the case to trial.
The bottleneck in this process isn’t courtroom drama. It is paperwork. A typical personal injury case involves thousands of pages of medical records, billing statements, police reports, expert opinions, insurance correspondence, and prior treatment history. A paralegal or junior associate must read every page, extract the relevant medical information, construct a chronological timeline of treatment, identify gaps in documentation, cross-reference billing codes against treatment records, and ultimately produce a demand letter: a formal document that presents the case to the insurance company and demands a specific dollar amount in settlement.
This process takes weeks or months per case. An attorney handling 100 active cases simultaneously, which is typical for a busy personal injury practice, cannot possibly give each case the level of detailed analysis it deserves. Cases settle for less than they should because the attorney didn’t have time to find the medical record that documented a crucial symptom, or because the demand letter failed to articulate the full extent of the damages in a way that would withstand the insurance company’s scrutiny.
EvenUp built an AI platform that does this work. The system ingests the complete case file, medical records, bills, police reports, imaging studies, pharmacy records, everything. It autonomously produces a comprehensive medical chronology, identifies missing documentation, detects treatment gaps that need to be addressed before the case is ready for demand, and generates a demand letter that presents the case with a level of thoroughness and analytical precision that most human-produced demand letters cannot match.
The platform is powered by what EvenUp calls Piai, a proprietary AI system trained on hundreds of thousands of actual personal injury cases and millions of medical records. This training data is not public. It is the accumulated knowledge of how cases like this one have been documented, argued, and settled across the American legal system. When EvenUp’s agent produces a demand letter, it is drawing on a dataset that captures the patterns of what works: which arguments move insurance adjusters, which documentation structures withstand defense challenges, which framing of damages produces higher settlements for which categories of injury in which jurisdictions.
The results have been staggering. As of October 2025, EvenUp had helped resolve more than 200,000 personal injury cases, securing over $10 billion in damages for injury victims. The platform processes 10,000 cases per week. More than 2,000 law firms use the platform, including 20 percent of the top 100 personal injury firms in the United States. The company raised $150 million in a Series E round in October 2025 at a valuation exceeding $2 billion, bringing total funding to $385 million. ARR has been doubling year over year.
But the number that captures what EvenUp does is this. Kyle Wright, Managing Attorney at Wisehart Wright in Ohio, reported that an initial insurance company offer of $50,000 turned into a $1.75 million settlement after using EvenUp’s Case Companion to systematically dismantle the defense’s arguments in real time. That is a 35x increase in the outcome for an injured person, enabled by an AI agent that could analyze the case with a depth and precision that no human attorney, handling a hundred other cases simultaneously, could match.
Sweet James, one of the largest personal injury firms in the United States, scaled past $500 million in annual case results with 70 percent year-over-year growth without adding headcount. Founding Partner Steve Mehr cited EvenUp as a key partner in that transformation.
What makes EvenUp particularly relevant to the themes of this book is the pricing model. In 2025, EvenUp launched all-in-one per-case pricing, a model that charges the law firm for each case that moves through the platform rather than per seat or per user. This is a pricing metric that ties directly to the value the agent creates. A law firm doesn’t care how many people log into EvenUp. It cares about how many cases the platform processes and how much better those cases settle. Per-case pricing aligns the firm’s cost with the firm’s revenue in a way that per-seat pricing never could.
The platform has expanded far beyond demand letter generation. EvenUp now offers what it calls a Claims Intelligence Platform that covers the entire case lifecycle: intake evaluation (assessing whether a new case is worth taking), case monitoring (continuously scanning for missing documentation and treatment gaps as treatment progresses), medical chronology generation, demand drafting, negotiation support, and settlement analytics. The agent doesn’t wait for the attorney to ask. It proactively identifies issues, flagging in 37 percent of client conversations at one firm that problems existed that the human team had not yet detected.
This proactive capability is what separates EvenUp from a tool. A tool waits for instructions. An agent acts on its own judgment within the boundaries of its domain. EvenUp’s agents monitor cases continuously, trigger actions when conditions are met, and surface problems before they become obstacles to settlement. The attorney’s role shifts from managing paperwork to making strategic decisions about cases that the AI has already analyzed, organized, and prepared.
EvenUp’s largest customer pays over $4 million annually, which works out to roughly $40,000 of EvenUp revenue for every employee at that firm. That metric illustrates the leverage the platform creates. The firm isn’t paying for software features. It is paying for an AI system that enables a smaller team to handle more cases at higher quality, producing better outcomes for injured people and more revenue for the firm.
The harness that makes this possible is deep and proprietary. The Piai system’s training on hundreds of thousands of real cases creates a knowledge base that no competitor can replicate by licensing a foundation model. The integration with case management systems like SmartAdvocate, Litify, and CasePeer allows the agent to operate within the firm’s existing workflow rather than requiring the firm to change how it operates. The settlement repository, a database of past settlement outcomes used for benchmarking and case valuation, gives the agent a sense of what a case is worth that is grounded in empirical data rather than attorney intuition.
EvenUp’s CEO, Rami Karabibar, has described the competitive dynamics in terms that resonate with the broader agentic AI landscape: “I don’t think there’s gonna be 100 players in this space. I think it’s going to be a winner-take-most dynamic.” His COO, Raymond Mieszaniec, was more direct: “It’s not winner-take-all. It’s the last man standing.”
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