What transactional lawyer doesn’t want to be able to leverage their firm’s past agreements for information that can help them today? Naturally, everyone wants it. US-based legal tech startup Centari’s goal is to make this happen and Artificial Lawyer reached out to Kevin WalkerCEO and Co-Founder, for more information.
First, let’s look at what Centari does. By using genAI to leverage and organize data from past deals, it seeks to help lawyers:
– ‘Unlock more deal flow: Don’t just tell clients you’re the best firm for the job. Show them. Enrich marketing materials and elicit RFPs with experience data that illustrates your unique expertise.
– Master the trading board: Visualize market trends, compare your opponents’ past positions, and achieve optimal terms for your clients with powerful competitive intelligence.
– Never search for precedents again – Experience state-of-the-art precedent searching, powered by structured data. Centari enhances documents with rich metadata to identify the exact agreement you are thinking of.
So how did this all start? Walker explains that he worked at leading US law firm Paul Hastings, but left after about a year and then worked at various companies, including as general manager of a startup.
“I always wanted to do something entrepreneurial and I could see that many things could be improved (with the business intelligence of lawyers) and that many things could be automated,” he says.
When generative AI arrived, Walker realized what was possible. He soon met CTO and co-founder Bryan Gilbert Davisand in March 2023 Centari was launched.
“After ChatGPT it was clear that it was now or never,” he adds. “I saw an opportunity to create something that would help lawyers with their data strategy, that would maximize the use of their own unstructured data.”
He also notes that as a general manager, he “had to buy legal technology and was frustrated that firms didn’t empathize with how difficult it is to be a transactional lawyer.” Centari is also the result of all those experiences.
The product
Walker notes that companies like Henchman (now part of LexisNexis) turn to a DMS to find bundled clauses that connect to something a lawyer is drafting, but they want to be more comprehensive than that.
As part of the above features, the goal is to provide lawyers with “what’s in the market” across the transactional field and offer key data on multiple aspects of certain types of transactions, such as what is the current period for the provision of profits in a certain industry sector?
“Knowledge is power and companies have that data, but it’s unstructured. Once it’s structured and clean, it can be used for all kinds of things,” Walker says.
In short, the philosophy is that once you have the right data, extract it, and make sense of it, you can use it in multiple “downstream use cases.” It’s just a question of how you want to take advantage of it.
And that makes a lot of sense. It’s an approach that Litera’s Foundation Dragon product is also taking.
In terms of technology, they have developed a broad multi-model engine that leverages different genAI systems, from Gemini, Claude and GPT, to some open source ones as well.
“We are very flexible and some customers want everything to run on their own servers, so we can use open source there,” he adds.
He also mentions that they are “evaluating the accuracy of each” and are interested in being part of a movement toward industry-wide transparency when it comes to the performance of genAI tools.
Where next?
They have raised $1.7 million in pre-seed funding, with the participation of Jack Altman (Sam Altman’s brother) among others. They are also looking for more funding to be able to grow.
However, Walker is keen to stress that raising money is not an end in itself.
“There are a lot of legal tech companies that are raising a lot right now, but our goal is to build a product around use cases, it’s not just about scaling the company,” he adds.
Broadly speaking, Walker says the goal is to “Build a full-stack transactional legal platform‘, which can compete with multiple point solutions at once. In short, there is ‘an opportunity to verticalize the whole stack’.
Beyond that, there is the emerging field of agent tools, where perhaps an AI agent can negotiate a contract for lawyers, not entirely on its own, but certainly handle a solid portion of it. They could leverage structured trading positions and past data to then flag the proposed contract, and agents would push it to a final point.
“The agent could even understand how the lawyer works (based on his or her previous work),” Walker concludes, foreseeing many further developments in the field of legal AI to come.
These are exciting times and it’s good to see new companies like Centari trying to push the envelope.