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🏜️ Mirage: Universal, relevance search over PDF documents at any scale. Unbounded by the limits of LLM context windows.

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Mirage

Mirage screenshot

AI-powered document search for PDF-heavy workflows. Built during the Mistral Worldwide Hackathon 2026.

Upload PDFs, ask questions in plain language, and get answers with page-level evidence — reviewable and traceable. Powered by PageIndex: Document Index for Vectorless, Reasoning-based RAG.

Founders

Repository Layout

Directory Description
srv/ Go backend API and indexing/retrieval pipeline
web/ React app for upload, query, and evidence review
marketing/ Astro marketing site
email/ Hono + Cloudflare Worker for waitlist capture
video/ Remotion project for video assets
docs/ System-of-record documentation

Quick Start

Prerequisites

Setup

cp srv/.env.example srv/.env    # then set MISTRAL_API_KEY
task setup                      # install dependencies
task dev                        # start API + web app

The web app runs at http://localhost:3000 and the API at http://localhost:2137.

Run task help for the full list of available commands (build, lint, test, codegen, etc.).

Limitations

  • PDF-only ingestion (no other file types yet).
  • Single-user MVP — no authentication.
  • Local filesystem storage, no encryption at rest.
  • Evidence ranges are section/page-level, not text spans.

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🏜️ Mirage: Universal, relevance search over PDF documents at any scale. Unbounded by the limits of LLM context windows.

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