Big String AI

Overview

Developers and data analysts kept hitting context window limits when trying to analyze large documents, codebases, or datasets with AI. We built BigStringAI, a service that allows users to submit massive amounts of text — entire repositories, full legal contracts, complete data dumps — and get intelligent analysis back. Available as both a chat interface and a REST API.

The Challenge

Processing hundreds of thousands of tokens requires intelligent chunking, context management, and result synthesis. Simply splitting a document and processing each chunk independently loses cross-references and global context. The system needed to maintain coherent understanding across massive inputs while keeping response times reasonable.

Our Approach

We built a hierarchical processing system. Input is first analyzed for structure (code files, document sections, data schemas). Then a map-reduce approach processes chunks with overlap, maintaining cross-references through an intermediate context layer. Results are synthesized by a final pass that has access to all intermediate findings. The API is designed for developer ergonomics with streaming responses and webhook callbacks for large jobs.

Key Features

• 100K+ token context processing
• Intelligent document chunking with overlap
• Cross-reference preservation
• Chat UI and REST API access
• Streaming responses for large outputs
• Webhook callbacks for batch jobs
• Usage analytics and rate limiting

Results

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