AI-Driven Document Intelligence for IT Solutions

Challenge

• Manual retrieval of SOW, BOM, and Quote documents from SharePoint was time-consuming and inefficient.

• Extracting structured data like product details, pricing, and specifications from unstructured documents was complex.

• Ensuring fast, accurate, and context-aware search results required optimized query processing.

• Lack of a user-friendly interface made document search and retrieval cumbersome.

• Secure authentication and role-based access control were needed to protect sensitive business information.

Solution

• Automated SOW, BOM, and Quote document retrieval from SharePoint using n8n workflows.

• Utilized OpenAI GPT to interpret and extract key data points, including pricing and product specifications.

• Implemented structured document breakdown for efficient retrieval and context-aware responses.

• Converted text into vector embeddings using OpenAI for fast semantic search.

• Stored vectorized data in Pinecone to enable real-time, relevance-based ranking and retrieval.

• Processed both structured (tables, lists) and unstructured (paragraphs, notes) data for comprehensive search coverage.

• Designed an AI-powered chatbot in React for seamless document queries and retrieval.

• Integrated the chatbot with backend workflows via AWS API Gateway for real-time responses.

• Defined optimized prompt structures to enhance AI-generated responses with precise document references.

• Implemented authentication and role-based access control to ensure secure document access.

Outcome

• 60% reduction in time spent retrieving and processing SOW, BOM, and Quote documents.

• 85% improvement in search accuracy with AI-powered vector search and contextual processing.

• 40% increase in operational efficiency through automated document ingestion and AI-driven query resolution.