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client success stories
Zoreza Global’s experts deliver exceptional generative AI results for clients all over the world
3 min read
Insurance
Automating manual workflows
Retrieval augmented generation (RAG) combines two powerful components: Information retrieval and generative model capabilities. One groundbreaking application of generative AI-powered RAG was in the insurance sector. Our client’s challenge was to transfer old insurance policies from a legacy system to a modern version. The massive volume of documents (dating back to 2005) from which data was traditionally extracted by hand, which took too long and occupied the valuable time of too many employees.
Our team expedited the process using RAG to develop an application, which enables analysts to interrogate the relevant data in a Q&A style. Generative AI (LLMs and word embeddings, in particular) increased efficiency and accuracy.
Empowered search via generative AI
The original workflow involved laboriously searching multiple documents and data sets. This provided a natural language interface that allows the user to "chat with their documents”.
Users can perform more complex queries with multiple criteria and see concise results, in real time. The LLM can be hosted in-cloud or on-prem, depending on data privacy demands.
Key benefits
Speed
What would have taken hundreds of employees several hours to complete has been reduced to a handful of staff and a few seconds. When searching the vector database, it takes just 38.3ms to return the closest matching section of a document for a single question (when searching over a million vectors).
User-friendly interaction
RAG allows users to request information in natural language and get the answer there and then, streamlining the user experience and boosting efficiency. No more navigating complex file systems or SharePoint databases.
Flexible querying
This technique enables the use of more complex, previously impossible queries. Queries like, “Show me all policies in the last 10 years with customers located in Birmingham, Liverpool and London with two or more cars” or “Compare the reinstatement interest across these products if the policyholder is 85 years old.” Users can mix and match search types, combining various complex search criteria into a single query instead of having to make numerous separate searches.
Modularity
One of the greatest advantages of the solution is that depending on data privacy needs, businesses can either use a hosted LLM, or an on-prem model. This flexibility ensures that the solution adapts to many requirement types.
Looking to the future
As generative AI possibilities escalate, approaches like RAG will redefine industries, delivering insights and enhancing productivity in ways previously unimagined. This project typifies the transformative power of generative AI in real-world conditions and reinforces the potential of leveraging technological advancements for better business outcomes.
The future of data interrogation is super-efficient, intelligent and generative.
Talk to us
Want to discover how RAG can take your business to the next level? Visit the Zoreza Global website or talk to one of our generative AI experts today.
