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Seattle-area startup Advocat is using artificial intelligence to help companies save time and money with their legal contracts.
Led by a former U.S. diplomat, Advocat’s AI-based legal contract generator uses templates based on existing company contracts and guardrails set by legal teams. Its software also provides a negotiation tracking tool. The idea is to eliminate repetitive work for legal teams, keep contracts up-to-date, and streamline business processes.
“Advocat is part of a movement to make the legal system more fair using technology, have a real impact on standardizing the way that contracts are made, and speed up the process to make it more accessible and affordable,” said CEO Pradnya Desh, a trained lawyer helped launch Advocate in 2019.
Advocat follows a usage-based pricing model that charges companies on a per-contract basis. The 10-person startup focuses on the most common contracts that U.S. companies need, but can train AI models for new types of contracts within a month, Desh said.
Earlier this month, Advocat won the Seattle regional event for the Startup World Cup and advanced to the global finale in San Francisco taking place this fall. The competition, hosted by Pegasus Tech Ventures, awards $1 million to the winning team.
Advocat has raised $2.2 million from investors, as well as the San Diego Angel Conference and Seattle Angel Conference
We caught up with Desh for the latest Startup Spotlight. Continue reading for her answers to our questionnaire. Answers were edited for brevity and clarity.
Our competitors and how we’re different: We have competitors in the market that have very large, heavy Contract Lifecycle Management (CLM) systems — they’re the opposite of product-led growth. To implement a large CLM, it takes months of a sales cycle and then after that, it takes months of onboarding time. During that onboarding process, those companies have to dedicate a full-time employee to assist with the onboarding, so it’s a very heavy lift from the customer side of things. We’re the opposite of that — if somebody decides to use Advocat, they can decide today and just start. So, we call ourselves the anti-CLM.
The smartest move we’ve made so far: Hiring great people. The team is who is with you for the long haul.
The greatest challenge in developing Advocat: Legal has a very high need for accuracy, so it’s very important to get the contracts right, protect data and make sure our system is secure. Those are all key considerations that we’ve had in developing it, so building a model that is as accurate as our customers need them to be while not letting data go from one part of the system into another part of the system was a challenge. It’s something that we made sure we did before even going to market, but our engineers spent quite a bit of focus on doing that well.
The biggest mistake we’ve made so far: Engineering takes a lot longer than then you expect it to take, and even if you expect it to take longer than you expected, it takes longer than that.
How the economic uncertainty is affecting our growth: We were raising in June so it felt very uncertain as to whether we would be able to close it in time. Seeing the macroeconomic situation, we made sure to close it as quickly as we could. We were worried that if we didn’t close it then, it could go on for a long time and as an early-stage startup, we don’t have a long time. So, it just made us act a lot quicker in closing a funding round.
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