NexusAI: Enterprise Knowledge Retrieval
A custom RAG pipeline and AI chatbot developed to help a 500-person enterprise search their internal documents instantly.
The Challenge
Our client, a massive logistics enterprise, was losing thousands of hours a year tracking down internal compliance protocols, employee handbooks, and shipping directives stored across scattered Google Drives and Confluence pages. They needed an intelligent AI assistant that could read their entire knowledge base and provide factual, cited answers to employees instantly. We built NexusAI: a highly secure Retrieval-Augmented Generation (RAG) system running entirely within their Virtual Private Cloud.
Key Features
Custom document ingestion pipeline for PDFs, Word files, and Confluence pages
Vectorization and storage using Pinecone for sub-second semantic search
A sleek, chat-based Next.js interface for employees to query the database
Cited sources: The AI tells users exactly which internal page it pulled the answer from
Role-based access: The AI respects user permissions and won't surface confidential HR data to standard employees
Technical Hurdles
Ingesting 10,000+ unstructured PDFs with varying layouts without losing data context
Preventing the LLM from "hallucinating" facts by strictly binding it to the retrieved context
Handling high-concurrent queries during peak morning hours without rate-limiting the OpenAI API
The Impact
Reduced average search time for compliance documents from 12 minutes to < 5 seconds
Saved the company an estimated $400,000 annually in lost productivity
Zero hallucination rate verified during human QA testing
Tech Stack
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