Long before generative AI could draft a contract in seconds, Adam Nguyen was spending 90-hour weeks reading them one clause at a time.
After graduating from Harvard Law School in 2002, Nguyen began practicing corporate mergers and acquisitions before moving in-house and later working at a private equity firm. Wherever he went, contract due diligence followed: vast collections of agreements that lawyers had to comb through under intense time pressure, searching for risks, liabilities and benefits.
“It was very painful, very tedious and very expensive,” Nguyen [pictured above] told Refresh Miami.
By 2011, Nguyen and a Harvard Law classmate believed machines could shoulder some of that burden. They collaborated with Columbia University researchers to commercialize technology using machine learning and natural language processing, then built eBrevia: a platform that could read large batches of contracts and produce summaries for junior associates to review.
The software reduced review time by 60% to 90%. Customers eventually included three of the Big Four accounting firms, and eBrevia expanded into work such as identifying revenue leakage buried inside corporate agreements.
Then Nguyen, alongside co-founder and CTO Jacob Mundt, sold the company. Donnelley Financial Solutions, a publicly traded strategic investor already on eBrevia’s cap table, acquired it in 2018. Nguyen departed soon afterward. But five years later, in December 2023, he and eBrevia’s former chief technology officer decided on an unusual second act: They bought it back.
Since regaining control, the pair has layered generative AI onto eBrevia’s earlier technology while retaining many longtime clients. A new product, DraftPro, moves beyond analysis, helping law firms draft agreements using their own precedents and institutional knowledge. Its playbook feature can also evaluate incoming contracts against a firm’s preferred positions.
That proprietary context is key. General-purpose models may know public information, but law firms and companies want AI that understands how they negotiate, draft and manage risk. Customizing models with private data, however, consumes tokens (read: money).
“A year ago, the conversation was about token maxing,” Nguyen said. Now corporate clients are imposing limits as spending on models, computing power, electricity and memory becomes clearer. The next phase, he believed, will be choosing the right model for each assignment rather than reflexively reaching for the biggest one.
Nguyen has watched enough AI cycles to temper optimism with caution. “There’s a bubble in legal tech, but also a lot of promise in the space,” he said. As CEO, his job is to innovate while identifying and minimizing risk.
He is doing that from Coral Gables. Nguyen moved from New York to Florida during the pandemic and, unlike many transplants, stayed. eBrevia followed, relocating its headquarters to Miami-Dade while operating remotely with a lean, 30-person global team.
The company is independent and funded by revenue, not venture capital – a structure Nguyen said lets it move quickly without answering to investors.
In an industry racing to spend more on intelligence, eBrevia is betting that survival may depend on something lawyers already understand: reading the fine print.
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