| Hi! We're publishing a special edition of the newsletter to bring you a deal scoop today. Startups that can cut down on costly paperwork for lawyers using generative artificial intelligence continue to draw investor dollars, despite the high costs of developing that software and the difficulties the startups face in acquiring exclusive legal data to train their models. The latest: San Francisco-based EvenUp, which develops AI software to help personal injury lawyers compile claims using medical documents and case files, is in talks to raise a new round of funding at a $1 billion valuation, according to a person briefed on the round. It's not clear whether that price includes the new investment. The company has spoken to current investor Bain Capital Ventures about leading the round, the person said. The round, if completed, would double the startup's valuation from its last, Series C investment led by Lightspeed Venture Partners. It would be EvenUp's third funding round in a little over a year. It's already raised about $100 million in funding. (The founders didn't have anything to say when we reached out for comment.) The discussions speak to strong investor interest in startups that are specializing in conversational AI for specific industries like law, healthcare and finance. Legal AI startups Leya and Luminance have also raised funding rounds in the last six months, according to The Information's Generative AI database. Concerns about high costs and limitations of their training data have tempered some enthusiasm for legal startups, however. Four-year-old EvenUp was generating around $35 million in annualized revenue as of July, with plans to reach more than $50 million in ARR by the end of the year, according to a person who met with executives. (Annualized revenue is a measure of the past month's revenue multiplied by 12.) That revenue implies investors are valuing the business at around 28 times the most recent annualized revenue figure, on the lower end of the revenue multiples AI startups have received recently. For instance, legal AI software startup Harvey said in July it had raised $100 million at a $1.5 billion valuation, a multiple that was 60 times its annual recurring revenue (or revenue from subscriptions) of $25 million. And OpenAI's fundraising efforts, which could value it at $150 billion, would amount to more than 37 times its annualized revenue, we reported Thursday. EvenUp may raise at a lower valuation multiple than some rivals because of its labor costs. The startup employs dozens of legal and medical experts who double-check the demand letters and medical history summaries its AI generates, to prevent any errors the AI might make, according to the person who has spoken to its executives. EvenUp's gross profit margins were around 50% as of July, the person said. That's significantly lower than traditional software businesses, which typically see gross margins in the mid-to-high 70 percentages, according to Meritech Capital, which tracks the performance of publicly-traded software companies. Those margins could improve over time as EvenUp's AI becomes less prone to making mistakes and as computing costs go down. Harvey also employs lawyers to evaluate the results its models produce, according to a person with direct knowledge of its operations. Other AI startups like Anthropic have faced similar concerns around their margins. Beyond labor costs, startups in the sector face challenges obtaining the specialized legal data that trains models to synthesize and generate legal documents. Expensive licensing agreements is one option; buying the data is another. Before Harvey raised its latest round, it had spoken to investors about raising $600 million in funding at a $2 billion valuation to acquire vLex, a 25-year-old legal research service, to use its legal data to improve its models. Prospective investors in Harvey balked at the price and worried that the acquisition wouldn't ensure Harvey could catch up to competitors, and the acquisition eventually fell through. | 
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