AI-Driven Document Intelligence for IT Solutions

A global IT infrastructure and networking solutions provider needed a faster, more efficient way to access SOW, BOM, and Quote documents. We developed an AI-powered chatbot that automates document retrieval from SharePoint using n8n workflows, enabling natural language search for instant access to critical information.

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.