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When authorized analysis firm LexisNexis created its AI assistant Protégé, it needed to determine one of the simplest ways to leverage its experience with out deploying a big mannequin.
Protégé goals to assist attorneys, associates and paralegals write and proof authorized paperwork and be sure that something they cite in complaints and briefs is correct. Nonetheless, LexisNexis didn’t need a normal authorized AI assistant; they needed to construct one which learns a agency’s workflow and is extra customizable.
LexisNexis noticed the chance to deliver the ability of enormous language fashions (LLMs) from Anthropic and Mistral and discover one of the best fashions that reply person questions one of the best, Jeff Riehl, CTO of LexisNexis Authorized and Skilled, informed VentureBeat.
“We use one of the best mannequin for the precise use case as a part of our multi-model strategy. We use the mannequin that gives one of the best consequence with the quickest response time,” Riehl stated. “For some use instances, that will likely be a small language mannequin like Mistral or we carry out distillation to enhance efficiency and scale back price.”
Whereas LLMs nonetheless present worth in constructing AI purposes, some organizations flip to utilizing small language fashions (SLMs) or distilling LLMs to turn out to be small variations of the identical mannequin.
Distillation, the place an LLM “teaches” a smaller mannequin, has turn out to be a well-liked technique for a lot of organizations.
Small fashions usually work greatest for apps like chatbots or easy code completion, which is what LexisNexis needed to make use of for Protégé.
This isn’t the primary time LexisNexis constructed AI purposes, even earlier than launching its authorized analysis hub LexisNexis + AI in July 2024.
“We now have used plenty of AI previously, which was extra round pure language processing, some deep studying and machine studying,” Riehl stated. “That actually modified in November 2022 when ChatGPT was launched, as a result of previous to that, plenty of the AI capabilities have been sort of behind the scenes. However as soon as ChatGPT got here out, the generative capabilities, the conversational capabilities of it was very, very intriguing to us.”
Small, fine-tuned fashions and mannequin routing
Riehl stated LexisNexis makes use of completely different fashions from many of the main mannequin suppliers when constructing its AI platforms. LexisNexis + AI used Claude fashions from Anthropic, OpenAI’s GPT fashions and a mannequin from Mistral.
This multimodal strategy helped break down every process customers needed to carry out on the platform. To do that, LexisNexis needed to architect its platform to swap between fashions.
“We might break down no matter process was being carried out into particular person parts, after which we might establish one of the best massive language mannequin to help that part. One instance of that’s we’ll use Mistral to evaluate the question that the person entered in,” Riehl stated.
For Protégé, the corporate needed sooner response instances and fashions extra fine-tuned for authorized use instances. So it turned to what Riehl calls “fine-tuned” variations of fashions, primarily smaller weight variations of LLMs or distilled fashions.
“You don’t want GPT-4o to do the evaluation of a question, so we use it for extra subtle work, and we swap fashions out,” he stated.
When a person asks Protégé a query a few particular case, the primary mannequin it pings is a fine-tuned Mistral “for assessing the question, then figuring out what the aim and intent of that question is” earlier than switching to the mannequin greatest suited to finish the duty. Riehl stated the subsequent mannequin may very well be an LLM that generates new queries for the search engine or one other mannequin that summarizes outcomes.
Proper now, LexisNexis largely depends on a fine-tuned Mistral mannequin although Riehl stated it used a fine-tuned model of Claude “when it first got here out; we aren’t utilizing it within the product at the moment however in different methods.” LexisNexis can also be excited about utilizing different OpenAI fashions particularly because the firm got here out with new reinforcement fine-tuning capabilities final 12 months. LexisNexis is within the technique of evaluating OpenAI’s reasoning fashions together with o3 for its platforms.
Riehl added that it might additionally take a look at utilizing Gemini fashions from Google.
LexisNexis backs all of its AI platforms with its personal information graph to carry out retrieval augmented era (RAG) capabilities, particularly as Protégé may assist launch agentic processes later.
The AI authorized suite
Even earlier than the appearance of generative AI, LexisNexis examined the potential of placing chatbots to work within the authorized {industry}. In 2017, the firm examined an AI assistant that may compete with IBM’s Watson-powered Ross and Protégé sits within the firm’s LexisNexis + AI platform, which brings collectively the AI companies of LexisNexis.
Protégé helps legislation companies with duties that paralegals or associates are inclined to do. It helps write authorized briefs and complaints which can be grounded in companies’ paperwork and information, counsel authorized workflow subsequent steps, counsel new prompts to refine searches, draft questions for depositions and discovery, hyperlink quotes in filings for accuracy, generate timelines and, in fact, summarize advanced authorized paperwork.
“We see Protégé because the preliminary step in personalization and agentic capabilities,” Riehl stated. “Take into consideration the several types of attorneys: M&A, litigators, actual property. It’s going to proceed to get increasingly more customized based mostly on the precise process you do. Our imaginative and prescient is that each authorized skilled can have a private assistant to assist them do their job based mostly on what they do, not what different attorneys do.”
Protégé now competes in opposition to different authorized analysis and know-how platforms. Thomson Reuters personalized OpenAI’s o1-mini-model for its CoCounsel authorized assistant. Harvey, which raised $300 million from traders together with LexisNexis, additionally has a authorized AI assistant.
