Document context layer for enterprise AI agents

Infratex reads PDFs, scans, tables and handwriting, and turns them into structured Markdown, JSON and cited answers your AI agents can work with.

Read the docs

Enterprises run on documents, not databases. The facts your agents need sit in contracts, filings, scanned forms and handwritten notes. Infratex reads every page and turns it into context your agents can search, reason over and cite.

Documents in.Context out.

Watch one page go through Infratex. It reads the layout, tables, handwriting, formulas and charts, writes them out as Markdown and JSON, indexes them, and answers your agent's questions with the page each answer came from.

Ranked first for table extraction on PulseBench-Tab (0.9636 T‑LAG, Infratex Standard).

Demonstration: Infratex reads page 14 of a 62-page facility agreement, detects its layout regions, writes them out as Markdown and JSON, and indexes them. An AI agent then asks questions and gets answers cited to the page.
  1. Parse
  2. Structure
  3. Index
  4. Retrieve
  5. Answer
facility-agreement.pdfpage 14 of 62
Infratex context layer
Your agentcalls Infratex over MCP

Ask

Built for teams that live in documents

What it reads, and what your agents get back

The same pipeline handles a clean annual report and a faxed claim form. You choose the output, and page numbers travel with the content.

It reads

Complex tables
Merged cells, nested headers and long tables keep their rows and columns.
Handwriting and stamps
Margin notes, signatures and filled-in forms come back as text.
Formulas
Equations come back as LaTeX.
Charts and figures
Each figure is captioned and described, and chart data is written out as a table.
Scans and photos
Skewed scans, faxes and photographed pages, as well as native PDFs.
More than 140 languages
Including pages that mix languages and scripts.

Your agents get

Markdown
Clean Markdown with a marker for every page, so each passage keeps its page number.
JSON in your schema
Define the fields you need and get them back typed.
A hybrid index
Vector search combined with the document's own structure.
Answers with sources
Responses grounded in your documents, with the pages they came from.
API and MCP
A REST API, and an MCP server your agents can call directly.

Ranked first on PulseBench-Tab

We ran Infratex Standard on the released PulseBench-Tab table extraction dataset and scored it with the official T-LAG scorer: 1,820 table samples in ten languages. It led on mean score and had the fewest severe failures.

0.9636
mean T-LAG score
9 of 10
languages won
6
samples below 0.50, the fewest of the systems tested
PulseBench-Tab, overall T-LAG (higher is better)
#SystemCoverageScore
1Infratex Standard100.0%0.9636
2Pulse Ultra 2100.0%0.9347
3LlamaParse Agentic94.0%0.7977
4Reducto Agentic78.8%0.7953
5Extend91.9%0.7626
6Azure Document Intelligence92.0%0.7614
7AWS Textract98.5%0.6034
8Unstructured100.0%0.3603

“The table parsing accuracy alone is lightyears ahead of other pipelines we benchmarked. It was the only solution that reliably parsed multi-page PDFs with nested grids without breaking.”

Head of AI Infrastructure, public fintech bank

Runs where your documents live

  • Managed cloud

    Use the hosted API with a key. Nothing to install or run.

  • Your private cloud

    Run Infratex inside your own VPC, next to the documents it reads.

  • On-premises

    An isolated container deployment for teams whose documents cannot leave the building.

Questions

What types of documents does Infratex support?

Native and scanned PDFs, multi-column documents, and page images (PNG, JPEG, WebP). Our vision models read each page as an image to recover reading order across complex column layouts.

How is this different from traditional OCR?

OCR reads a page line by line and returns raw strings, losing table alignment and the hierarchy of the page. Infratex reads the whole page at once and keeps its structure: table grids, LaTeX equations, headings and figures.

What output formats does Infratex generate?

Hierarchical Markdown with structured tables, marked figures and a marker for every page, plus JSON shaped to any extraction schema you define. Your models and vector stores get clean text without formatting noise.

Can Infratex run in our private VPC or on-prem?

Yes. Alongside our managed cloud, we support private VPC setups and isolated on-premises container deployments for teams with strict medical, legal or financial compliance requirements.

See it on your own documents

Tell us where your document pipeline breaks and upload a few samples. We'll run them through Infratex and walk through the structured output with you on the call.

Demo request

Pick a time

Pick a day and a time. You'll get a calendar invite by email straight away, and the meeting link before the call.

Your details

Pick a day and a time to continue.