---
title: "AI Research Platform"
description: "Production RAG system indexing 100M+ documents from 20K+ sources with sub-300ms p99 latency. Case study from BlueField Digital."
canonical: https://bluefielddigital.com/case-studies/ai-research-platform/
---

# AI Research Platform

AI Engineering · Data Engineering

## Overview

A production RAG system that indexes 100M+ documents from 20,000+ sources and makes them queryable through an LLM-powered research assistant, with sub-300ms p99 latency at web scale.

## Challenge

The client needed 100M+ documents (academic papers, patents, regulatory filings, and news articles) consolidated into a single searchable knowledge base. Keyword search missed semantic connections between documents and couldn't handle the volume or velocity of new data arriving daily.

## Solution

We built a multi-stage ingestion pipeline that normalizes, chunks, and embeds documents into a vector database. A hybrid retrieval system combines dense vector search with sparse keyword matching for high recall and precision. The LLM-powered research assistant synthesizes results into coherent answers with source citations, and the entire system is optimized for throughput with async processing, batched embeddings, and intelligent caching.

## Results

100M+

Documents indexed

20K+

Sources integrated

<300ms

p99 query latency

99.9%

Uptime SLA

## Tech Stack

Python LangChain OpenAI Pinecone Elasticsearch Redis AWS Lambda S3 SQS Docker

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