Changelog

Saturion Updates

Latest updates, improvements, and new components added to Saturion.

Update

May Saturionstream Update

The /parse endpoint turns documents into clean, structured data for AI agents and RAG pipelines. Powered by a new Rust-based engine that's up to 5x faster, it works across PDFs, Word docs, spreadsheets, and more.

Added
  • Clean, LLM-ready output — Get back Markdown, JSON, or a summary, with tables and reading order preserved. No post-processing required.

  • Rust-based engine — A high-performance Rust core delivers up to 5x faster parsing, cutting latency in document ingestion and embedding workflows.

Bug Fixing

May Surge Update

Saturion web-agent is an open framework for building AI agents that search, scrape, and interact with the web. Powered by the same architecture behind our /agent endpoint.

Added
  • Bring any model — Anthropic, OpenAI, Google, or your own. You control the logic, tools, and infra.

  • One command, full stack$ firecrawl create agent gives you /scrape, /search, and /interact in a plan-act loop, parallel sub-agents for concurrent research, and your choice of Streaming UI, API server, or library templates.

  • Teachable by design — Add Skill playbooks and your agent learns reusable routines. Paginate e-commerce sites, run multi-source research, and extract structured data your way.

Update

April Momentum Update

Fire-PDF is a Rust-based parsing engine that converts any PDF - scanned, text-based, or mixed - into structured markdown, up to 5x faster.

Added
  • 5x Faster — Our open-source Rust library pdf-inspector classifies each page in milliseconds and picks the fastest extraction path. Pages are processed in under 400ms on average.

  • Layout-Aware Accuracy — A neural document layout model detects tables, formulas, text blocks, and headers individually. Tables get full markdown output, formulas are preserved in LaTeX, and reading order is predicted neurally.

  • Zero Configuration — Every PDF sent through Firecrawl's API now goes through Fire-PDF automatically.

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