AI-Powered Integration of Unstructured and Tabular Data

A manufacturing company was looking to connect document-based content and structured business data to gain faster, more accurate insights.

The customer struggled to integrate unstructured documents (e.g., PDFs, contracts, reports) with tabular business data. Key issues included incomplete data extraction, loss of document structure, and time-consuming update processes. These limitations made it difficult to generate accurate, timely insights for decision-makers.

Brimit built an AI-powered data integration platform that seamlessly combined structured and unstructured data, making it accessible through natural language queries. Designed for scalability, real-time performance, and contextual understanding, the platform includes the following AI-driven capabilities:

• Used a Retrieval-Augmented Generation (RAG) approach to connect documents and data with full context
• Added smart update tracking with document fingerprinting and change data capture mechanisms to process only modified content
• Enabled natural language queries using Text-to-SQL, so anyone could ask complex questions without writing code
• Preserved structure and contextual relationships within documents to keep AI answers clear and accurate

• 70% faster data preparation with AI automated extraction, matching, and context preservation across document and database sources
• Context-aware document integration maintaining structure and meaning across multi-page documents for reliable insights
• AI-powered natural language analytics enabling business users to run cross-format queries without writing code