Source: Microsoft
UBS’s in-house legal team must find very specific information, like a clause or regulation, across a library of 26 million legal documents in multiple languages. Looking to empower its legal team to focus on more value-added work and streamline the time spent searching through documents, the company chose to build its solution on Microsoft Azure OpenAI Service and Azure AI Search. The resulting knowledge management solution, Legal AI Assistant (LAIA), offers semantic search functionality at scale using metadata identification from the underlying storage systems to help employees pinpoint phrases, clauses, and paragraphs using natural language and semantic similarity, rather than keyword matching.
UBS employees can now locate information much more quickly and easily than they had with the prior search tools produced. Employees are finding productivity gains, thanks to the improved search experience and accuracy provided by LAIA.
UBS is expanding the tool globally, all while respecting the tight regulations placed on the industry, along with the needs of its employees. “Moving to a system like this takes training,” says Felicia Efta, Legal Counsel Asset Management, Head of Alternative Funds EMEA at UBS. “We need to switch from keyword search to descriptive search and learn prompting skills. That’s why we’ve also developed bespoke training focused on helping employees to improve their queries and better utilize LAIA.”
“We did a lot of upfront planning to ensure the solution would fit within the highly regulated UBS environment and work for our use case,” says Ilias Fotopoulos, Chapter Lead, AI & Data Engineer at UBS. “At UBS, we were early adopters of Azure AI technologies, and they’ve only gotten better over time. They’ve helped us streamline search across millions of documents at scale and with speed.
“Deploying Microsoft AI technologies has made our legal teams’ work easier and faster,” says Vlad Stoian, Product Owner for the Legal AI Assistant at UBS. “We plan to enhance LAIA further by converting unstructured data to structured data to make it easier to search and filter documents based on specific criteria. We want to keep unlocking more use cases and improve LAIA’s overall utility.”
“The performance of Azure AI Search exceeded our initial prototype’s results, and it’s helped us build one of the largest-scale knowledge retrieval systems at UBS,” says Fotopoulos. “That just reinforces our certainty that collaborating with Microsoft on this project was the right decision.”
Read the full article: https://www.microsoft.com/en/customers/story/22961-ubs-ag-azure-ai-search
