AI Document Processing Benchmark

Before spending money on traffic, FileDigest should be judged by completed jobs, readable output, and repeatable artifacts. This benchmark page gives buyers and operators a simple way to test whether document preparation is good enough for real AI work.

Benchmark checklist

Run one small packet and inspect:

• file count accepted
• page count detected
• processing outcome for each file
• generated digest.md
• generated manifest.json
• token estimate
• warnings or failed files
• download access control
• whether the digest can be reused in ChatGPT, Claude, RAG, or an AI coding tool

Suggested first packet

Use a packet with:

• one simple PDF
• one scanned or OCR-heavy PDF if your plan supports OCR
• one DOCX file
• one plain-text or Markdown note
• one ZIP containing mixed files

What good looks like

The output should make source boundaries visible, preserve enough structure to review, and show failures in the manifest instead of pretending every file was perfect.

What FileDigest is optimizing for

FileDigest is not a black-box summarizer. The goal is AI-ready document preparation: inspectable Markdown, structured manifests, private downloads, and repeatable context packs.