Overview
In the rapidly evolving BFSI (Banking, Financial Services, and Insurance) sector, the ability to harness enterprise knowledge at scale has become a strategic imperative. DeltaDot AI partnered with a leading BFSI conglomerate to deploy an Enterprise Knowledge Automation solution powered by Large Language Models.
Client Background and Challenges
The client is a diversified BFSI group operating across retail banking, insurance, asset management, and fintech. With over 50,000 employees and operations in 12 countries, the organization manages petabytes of data across legacy systems, cloud platforms, and third-party services.
- Data Silos: knowledge trapped in departmental systems — CRM, ERP, DMS, and email archives.
- Regulatory Complexity: constantly evolving compliance requirements across jurisdictions.
- Customer Expectations: rising demand for personalized, real-time service across digital channels.
- Operational Bottlenecks: manual document processing, slow onboarding, and fragmented workflows.
Solution Highlights
DeltaDot AI proposed a modular Enterprise Knowledge Automation Platform powered by domain-tuned LLMs, designed to:
- Ingest and index unstructured documents from multiple sources.
- Enable semantic search and contextual Q&A using LLMs.
- Automate document summarization and classification.
- Integrate with existing workflows via APIs and secure connectors.
- Ensure compliance with BFSI-grade security standards.
Business Impact
Conclusion
By deploying LLMs in a secure, explainable, and scalable manner, the BFSI organization achieved a 60% reduction in time spent searching for information and a 40% improvement in customer-query resolution accuracy — demonstrating how LLMs can be operationalized beyond experimentation.