NeoGrowth Credit Pvt. Ltd. is a technology-driven NBFC focused on providing fast and accessible financing solutions to MSMEs across India. With a strong reliance on data and internal knowledge systems, the organization required a more efficient way to access and utilize information across teams.
Business ChallengeNeoGrowth faced significant inefficiencies due to fragmented knowledge systems and limited data accessibility. Policies and documents were scattered across multiple repositories, while business users depended heavily on HR and data teams for routine queries. Non-technical users struggled to access structured data, leading to delays in reporting and decision-making. Additionally, the lack of governance and unified access created security risks and operational inefficiencies.
Goals & ObjectivesThe objective was to build a secure, unified platform that could provide seamless access to both unstructured documents and structured data. The client aimed to enable self-service analytics, reduce dependency on internal teams, improve decision-making speed, and ensure strong governance and data security.
Solution ApproachWe developed a Generative AI-powered virtual assistant on AWS, combining Retrieval-Augmented Generation (RAG) and Text-to-SQL capabilities into a single conversational interface.The solution enabled users to retrieve policy documents and organizational knowledge through semantic search while also allowing natural language queries on structured data stored in Amazon RDS. An intelligent orchestration layer routed user queries dynamically to the appropriate processing pipeline, ensuring a seamless user experience.The platform was deployed within a secure VPC environment, with strict access controls, encryption, and governance mechanisms to ensure compliance and data privacy.
Implementation ApproachThe solution architecture integrated document storage, vector search, and database querying into a unified system. Organizational documents were ingested, processed, and indexed for semantic retrieval, while a validation layer ensured safe execution of AI-generated SQL queries. Chat history and context management enabled conversational continuity, and monitoring systems ensured performance visibility and reliability. Security was enforced through role-based access, private endpoints, and enterprise-grade authentication mechanisms.
Results
The solution significantly improved information accessibility and operational efficiency across the organization. Employees were able to retrieve both documents and data instantly through a single interface, eliminating dependency on HR and data teams for routine queries. Decision-making became faster and more data-driven, with real-time access to insights. The platform enhanced security and governance while delivering a seamless, unified user experience, ultimately transforming how the organization interacted with its knowledge and data systems.
