AI Document Intelligence Platform

Ask questions directly to your PDF library — get cited, structured answers in seconds.

Next.js 14OpenAIPineconePostgreSQLTailwind CSS

ai-document-intelligence.app

Overview

Document-heavy workflows — legal, financial, compliance — require analysts to manually read through hundreds of pages to find specific information. This platform removes that bottleneck entirely by making any document collection instantly queryable.

The Problem

Professionals working with large document libraries spend disproportionate time searching for information that is technically already there — just not instantly accessible. Manual search misses context and takes hours.

The Solution

PDFs are chunked, embedded, and stored in Pinecone. A query interface uses RAG to retrieve the most relevant chunks and synthesize answers with page-level citations. A secondary extraction mode pulls structured tables from specific document types.

Key Features

PDF Ingestion Pipeline

Upload PDFs; documents are parsed, chunked into semantically meaningful segments, and embedded using OpenAI's embedding model.

Vector Search via Pinecone

Embeddings stored in Pinecone enable sub-second semantic retrieval across thousands of pages.

Cited Q&A

Every answer includes source references — document name, page number, and quoted excerpt.

Structured Data Extraction

Extracts tables, figures, and key fields from standardized document formats into JSON output downloadable as CSV.