SEATTLE--(BUSINESS WIRE)--Lexion today announced a seed round of $4.2 million and launched its AI-powered solution for managing contracts. Developed at the Allen Institute for Artificial Intelligence (AI2), Lexion helps legal teams track key obligations in their contracts automatically and without slow and expensive document review. The easy-to-use and reliable system is aimed at high-growth emerging companies, and established players that typically have dozens to thousands of customer, vendor, and employee agreements to manage, but often lack the resources to do so.
Founded by serial entrepreneur Gaurav Oberoi, AI technology leader Emad Elwany, and engineering veteran James Baird, Lexion is applying cutting edge AI to ensure that companies don’t miss a “gotcha” clause, or spend hours of expensive outside counsel time in reviewing piles of contracts. Lexion’s platform can ingest all of a company’s contracts, automatically extract dozens of key terms, and deliver an organized repository of agreements that can be filtered, sorted, and searched across -- all in a matter of hours. The company’s proprietary natural language processing (NLP) engine can rapidly be trained to extract previously unseen clauses or new document types, ranging from insurance agreements to commercial real estate documents.
“Contract management is a pain point for every organization. Whether you manage 30 or 10,000 agreements, you still need to keep track of key obligations,” said Oberoi, Lexion’s Co-founder and CEO. “Yet, the most common approach – searching through file folders, reading through hundreds of pages of legal text, tracking terms in spreadsheets, and manually emailing reminders – is not scalable for any organization and often results in missing critical obligations and opportunities, while draining significant management time and resources. We are excited to solve this problem with cutting-edge automation, packaged in an intuitive product.”
The funding highlights the growing need for effective contract management across legal, sales, procurement, and finance teams. Organizations lose, on average, 9% of revenue every year due to poor contract management through erroneous overpayments, failure to apply discounts, and missed expirations, according to research by the International Association for Contract & Commercial Management (source).
“Gaurav, Emad, and James are just the kind of entrepreneurs we love to back: smart, customer obsessed and attacking a big market with cutting edge technology,” commented Tim Porter, managing director, Madrona Venture Group, who is also joining the company’s board. “AI2 is turning out some of the best applied machine learning solutions, and contract management is a perfect example – it’s a huge issue for companies at every size and the demand for visibility into contracts is only increasing as companies face growing regulatory and compliance pressures.”
“We are excited about Lexion because it will enable legal teams to manage their contractual obligations proactively rather than reactively, increase awareness of compliance and risk exposure across the organization, and increase the speed and efficiency of major transactions,” commented David Wang, Corporate Strategic Innovation Counsel, WSGR. “In our first-hand evaluation of legal analytics solutions, we found that Lexion outperformed the market across a range of criteria relevant to understanding legal contracts, giving us confidence in their ability to produce significant value for our clients.” As part of the funding, Wang will join Lexion’s board.
In contrast to expensive legacy contract management systems that require complex setup and training, Lexion focuses on rapid onboarding, affordable subscription pricing, and an easy-to-use interface that users can pick up intuitively. Out-of-the-box, Lexion can identify and extract dozens of key terms in contracts, such as termination notices, renewal dates, and payment terms. For a small additional fee, companies can request custom models to automatically extract information particular to their business or industry.