OmniAI Knowledge & Document Assistant
OmniAI empowers legal, compliance, and enterprise operational teams to query thousands of complex technical documents, contracts, and internal handbooks using natural conversational questions.
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Business Challenge
Enterprise research staff lost hundreds of hours manually searching through dense 200-page PDF policy documents and technical specifications to verify regulatory compliance.
Key Objectives
Our Engineered Solution
We engineered an intelligent Retrieval-Augmented Generation (RAG) platform with localized document chunking, embedding storage in Pinecone vector DB, and a conversational Next.js interface.
System Architecture Overview
Documents are processed by a background worker into overlapping token chunks, converted to vector embeddings, stored in isolated namespaces, and matched against natural language queries in real time.
Key Features & Functional Highlights
- Drag-and-drop batch document upload with instant progress feedback
- Contextual search with exact inline text highlighting and page references
- Conversational memory with exportable Q&A summary transcripts
- Tenant-isolated vector collections ensuring zero cross-data contamination
Technologies Used
Tech Stack Breakdown
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