Millions of personal injury cases are settled in the U.S. every year, as few go to trial — but the vast majority are kept under wraps. This leaves lawyers guessing what they should propose as a settlement price, oftentimes resulting in victims being undercompensated.

It’s what led Rami Karabibar to launch EvenUp, a startup that taps AI to generate legal documents to assess injury cases. The platform, aimed at customers in the legal field, attempts to use raw case files, including medical records, police reports and bills, to create letters arguing for proposed compensation.

“We’re on a mission to level the playing field in personal injury cases,” Karabibar, who previously worked across private equity, venture capital and venture-backed startups, said.

Karabibar co-founded EvenUp with Ray Mieszaniec, a two-time entrepreneur, whose father was permanently disabled after being hit by a car involved in a police chase. Mieszaniec’s family got just 10% of the average payout for that type of accident — partly because their lawyer didn’t know what the appropriate compensation should be.

EvenUp aims to tackle all categories of personal injury cases, including motor vehicle accidents, police brutality, child abuse and even natural disasters. To do this, Karabibar, Mieszaniec and EvenUp’s third co-founder, Saam Mashhad (a former litigator), built a database of private settlements — including hundreds of thousands of medical records — and trained an AI to estimate fair compensation based on the details of each case.

EvenUp’s platform extracts the relevant info from documents and organizes them into templated “demand packages,” which state the legal and factual basis for a personal injury claim and include a demand for compensation. Designed to be a self-service solution for lawyers, paralegal staff and law firms, EvenUp summarizes notes and copies of raw records into medical digests “optimized for injury law.”

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“The more documents and cases we see, the better we are at preparing demand packages, and the better we are at increasing case outcomes and reducing costs,” Karabibar said. “EvenUp reaches deeper in the legal workflow with a higher bar for accuracy than other AI assistants, from extracting data out of raw documents, to valuing what cases are worth, to generating final demand packages that bring that all together.”

As Karabibar alluded to, EvenUp isn’t the only startup applying AI to the tedious — and monotonous — task of drafting legal documents. Lawyaw, which emerged from stealth several years ago, is building software to automate the process of customizing standard documents like NDAs and wills. Elsewhere, Atrium’s software digitizes legal paperwork and builds apps on top to speed up fundraising, commercial contracts, equity distribution and employment issues.

But EvenUp claims that it’s one of the first to tackle personal injury — a law practice area not necessarily held in high regard. So-called “settlement mills,” which charge between 33% to 40% of total awarded compensation, settle a high volume of cases without necessarily focusing on maximizing the value of each claim.

Mieszaniec implies that EvenUp could change this by normalizing the practice of AI-aided personal injury litigation.

“By harnessing the potential of technology, we can create a future where the pursuit of justice is not marred by financial pressure or the representation you have,” Mieszaniec said via email. “It’s time to embrace innovative solutions that streamline the claims process, empower individuals, humanize the process and ensure that no one walks away with a fraction of what they deserve. That’s why we built EvenUp: to level the playing field for personal injury victims.”

EvenUp appears to have won over investors, who recently pledge $50.5 million in the company at a $325 million valuation (according to a source familiar with the matter). Bessemer Venture Partners led the latest round, a Series B, with participation from Bain Capital Ventures, Behance founder Scott Belsky and legal tech firm Clio, bringing EvenUp’s total raised to $65 million.

But can the tech live up to its promises — and address the outstanding legal and ethical implications?

With any AI tech, bias is a major concern. Algorithms trained on biased data can amplify those biases, perpetuating existing inequalities and injustices. For instance, a 2016 ProPublica analysis found that a widely used algorithm was twice as likely to misclassify Black defendants as presenting a high risk of recidivism than white defendants. One can imagine EvenUp’s AI recommending artificially high or low amounts of personal injury compensation as a result of dataset imbalances.

And what about privacy? EvenUp hasn’t disclosed where it sourced the medical and personal injury documents that it used to train its AI — nor whether it took steps to notify the original owners of those records.

That’s assuming once again that the tech works as advertised, even. If there’s any overarching takeaways from the generative AI boom, it’s that even the best AI algorithms today are far from perfect. (See: Microsoft’s Bing chatbot spouting vaccine misinformation and writing a hateful screed from the perspective of Adolf Hitler.)

If EvenUp’s customers share these concerns, it’s not obvious from their rush to adopt the platform. Karabibar claims that EvenUp counts “top trial attorneys” and “America’s largest personal injury law firms” among its customers and that it’s “close to profitable.”

Some, no doubt, are chasing after the chance to reduce filing expenses while maximizing returns. Karabibar doesn’t deny this.

“Injury attorneys are contingency-based, where they make a fixed percentage of the value of the case. Any increase in case outcomes directly impacts their revenue, while also increasing the amount clients receive,” he said.

But Karabibar also makes the case — rather optimistic, in my view — that automating aspects of the filing process could encourage litigators to “concentrate more on the human side of their work.” He’s also careful to suggest that EvenUp won’t replace lawyers outright. But, reading between the lines a little, it’s hard not to see how some paralegals, most of whom work on a contract basis, might find themselves out of a job if the tech were ever to be adopted on a mass scale.

“They’ll be able to support injury victims through the legal process, and advocating for the equitable outcomes their clients deserve,” he said.

We’ll see if that’s the case. In any event, EvenUp has broad ambitions, with plans to cover document generation in both the pre-litigation and litigation stages customized to each firm, jurisdiction and case type. Karabibar believes that EvenUp will eventually be able to handle 70% of the key documents in the personal injury law workflow.

“We are well-positioned to continue growing despite the turbulent economy, and we believe our products will only become more essential as time goes on,” Karabibar said. “Legal drafting has seen a fundamental step-change given the advent of generative AI. Legal professionals will need to be quick to adapt to this change or be competed out of the profession by more tech-savvy competitors.”