AI RAG for Enterprise: 95% Faster Search with LangGraph
Enterprise Software

AI RAG for Enterprise: 95% Faster Search with LangGraph

Reduced internal information retrieval time by 95% while centralizing data from 3+ fragmented sources.

The Challenge

The client, a high-growth enterprise software firm, managed a massive repository of technical documentation, training videos, and corporate assets across disconnected silos including Microsoft OneDrive, YouTube, and localized server clusters.

Core Problem

Engineers and support staff were spending up to 6 hours per week manually searching for specific technical answers. This fragmentation resulted in a 12% increase in duplicate support tickets and significant 'knowledge leakage' as critical insights remained buried in hours of video content and nested cloud folders.

Without a centralized intelligence layer, the client faced mounting operational costs and a projected 20% slowdown in product deployment cycles due to the inability to rapidly onboard new developers and resolve complex technical queries.

The Solution

EnDevSols architected a high-performance Retrieval-Augmented Generation (RAG) backend utilizing FastAPI for asynchronous processing and LangGraph for complex, stateful agentic workflows. We built a custom ingestion engine that autonomously syncs and indexes data from OneDrive and YouTube into a Qdrant vector database, transforming passive assets into a searchable, semantic knowledge graph.

Secret Sauce

Our unique 'Multi-Modal Ingestion Engine' didn't just index text; it automatically transcribed and semantically chunked video content and cloud documents in real-time. By integrating granular token-usage tracking and a custom admin dashboard, we gave the C-suite full visibility into AI operating costs and data provenance—transparency that standard 'out-of-the-box' RAG solutions lack.

Tech Stack

FastAPILangGraphQdrantPythonOpenAI GPT-4Microsoft Graph APIJWT AuthenticationDocker

Key Results

Hard Metrics

  • 95% reduction in information retrieval time for technical teams
  • 100% automated synchronization across YouTube, OneDrive, and local repositories
  • 22% reduction in operational overhead via granular token monitoring and optimization

Values & Impact

  • Significant boost in developer morale by eliminating repetitive search tasks
  • Enhanced data security posture through robust JWT-based authentication and audit logs
  • Improved accuracy in support ticket resolution
"EnDevSols didn't just build a chatbot; they built an enterprise nervous system. Our teams now have instant, unified access to the collective brain of the company. The ROI in terms of time saved was visible within the first month."
CTO, Global Enterprise SaaS Provider

Core AI Services Used in Projects Like This

RAG Systems & AI AssistantsDocument Q&A, knowledge bases, enterprise search
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AI Agents & Workflow AutomationCRM agents, document processing, automation
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AI Product Engineering & AI SaaSAI MVPs, full-stack AI products, SaaS features
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AI RAG for Enterprise: 95% Faster Search with LangGraph | Case Study | EnDevSols