AI Document Intelligence & Voice Assistant

Natural-language search across compliance documents, paired with automated outbound voice reminders.

Industry:Compliance
Our Role:Backend Specialist / DevOps Engineer

Project Overview

Compliance teams needed answers out of long PDFs without reading them end to end. A RAG pipeline built on Amazon Bedrock with OpenAI vector storage answers natural-language questions across multi-page documents, and a voice layer using Vapi AI webhooks with Node-cron scheduling places outbound appointment confirmation calls automatically.

Quick Facts

Technologies
Amazon BedrockOpenAI APIVapi AINode.js

Answers buried in multi-page compliance documents

Compliance material sat in long PDFs that had to be read manually, while appointment confirmations depended on someone remembering to call.

Multi-page PDFs with no practical search
Natural-language questions needing grounded answers
Manual, easily missed outbound confirmation calls

RAG retrieval plus scheduled voice automation

Documents are embedded into vector storage and queried through a Bedrock and OpenAI RAG pipeline, returning answers grounded in the source text. Vapi AI webhooks driven by Node-cron handle outbound appointment confirmations on schedule.

Our Approach

Built a RAG pipeline with Amazon Bedrock and OpenAI vector storage
Answered queries grounded in multi-page PDF content
Integrated Vapi AI webhooks and Node-cron for outbound confirmations