One upload turns your documents
into AI-ready knowledge

Collection, conversion, review, and delivery.
AI Data Foundry gets your document data ready for AI.

300 welcome credits · API key issued the moment you join

Soaring costs and operational risk — time to rewrite the playbook for AI adoption

Time and token costs that pile up when documents are processed repeatedly

Token costs on every question

Each time you ask, the AI re-reads the document from scratch — the same tokens, billed again and again.

Generic AI flattening tables and charts in Word, PowerPoint, and Excel files

Document formats generic AI can't read

Generic AI flattens the tables, charts, and layouts in Word, PowerPoint, and Excel files — structure and meaning get lost.

The burden of building and operating a document conversion system in-house

Build it yourself, own the maintenance forever

A DIY pipeline for conversion, review, and updates means dedicated engineering — and operations that never end.

Same documents, lower costs

Well-prepared documents cut your token usage.

Without AI Data Foundry

Feed in whole files, and needless costs pile up

Image-heavy tokens inflate usage and cost
The same cost comes back with every question
Tables and structure parse differently every run
AI chat
Drop here
PDF business-plan.pdf · attached as image
Thinking $0.00
Ask anything
PDF
business-plan.pdf
2.4 MB · 12 pages

* Actual savings vary by document type and the model you use.

Prepared with AI Data Foundry

Feed in structured data, and costs go down

Only the text that matters — far fewer tokens
Tables, headings, and reading order stay intact for consistent answers
More documents and more questions mean bigger savings
PDF
business-plan.pdf
2.4 MB · 12 pages
ADF API · /v1/ingest
POST /v1/ingest ← business-plan.pdf
Structured conversion · 12 tables · 38 headings · reading order preserved
AI collects only the text it needs
Ingest complete — spent $0.02

Use cases

Grant announcement processing workflow Running
📥 Auto-collect announcements3 new postings from the grants portal — 2026_AI_Voucher_Program.docx Done ✓
📄 Parse & structure12 tables · 38 headings · attached forms extracted, structure intact Done ✓
🤖 AI summary"SMBs eligible, up to $150K in funding, applications close Jul 31" — 3-line brief Done ✓
🏷️ AI classification & hand-offTagged #grants #AI-voucher #deadline-soon and routed to the right team Done ✓
Enterprise IT · DX

From download to AI summary, document work runs itself

📥 Auto-collect 📄 Parse & structure 🤖 AI summarize & classify
Result Every new announcement arrives already summarized, tagged, and routed straight to the right person.
See it with your documents →
Desktop AI harness + AI Data Foundry (MCP)
Turn this quarter's meeting notes and reports into a wiki
Calling AI Data Foundry via MCP — parsing Meeting_Notes_0712.docx and 29 more…
Markdown conversion complete → wiki/meetings/2026-Q3.md created
📚 LLM wiki updated — 30 documents indexed, ready for AI search & citation
Individual professionals

Pair your desktop AI with AI Data Foundry, and build your own LLM wiki

🖥️ Connect desktop harness ⚙️ Convert with AI Data Foundry 📚 Build LLM wiki
Result The Word docs and PDFs piling up on your drive become your own wiki your AI can search and cite.
Get your API key →

See it for yourself

PREVIEW Security Plan.docx 미리보기
Structured Output

Any format in, one consistent structure out

DOC
DOCX
PPT
PPTX
XLS
XLSX
PDF
IMG
ODT
TXT
JSON
XML
MD

14+ input formats · JSON / XML / Markdown out — Word, PowerPoint & Excel handled natively, structure intact

Connect the blocks, and document processing runs on its own

Wire up analysis → classification → transformation → review → delivery with clicks. New documents re-run the flow automatically.

For critical documents, a human makes the final call

Polish structure and tags with the refinement tools, then have owners give critical documents a final review on the web. Review history compounds into quality data tuned to your organization, and reviewers can be assigned by member or group.

wireless-sensor-networks.pdf 1 / 8|71%
Document under review
Tag list
Saved ✓
<h1>Tag
Simulation-based optimization of communlcation protocols for large-scale wireless sensor networks|
<p>Gyula Simon, Péter Völgyesi, Miklós Maróti
<p>Vanderbilt University
<p>Abstract — The design of reliable, dynamic, fault-tolerant services

Web, API, or MCP — plug in the way you already work

Business users click, developers call the API, AI agents connect over MCP. However a job runs, you can inspect and review it on the web.

The more documents you have, the bigger the difference

0.146s
Processing time per page
99.3%
Certified OCR accuracy (TTA)
14+
Supported input formats

Pages processed per minute

Industry-leading bulk throughput

AI Data Foundry
411
Company A
184
Global Co. B
46
Global Co. C
17

Pages converted per equal credit spend

* Based on a 1-year Enterprise subscription

AI Data Foundry
300
Company A
226
Global Co. B
120
Global Co. C
104

* Token and cost savings vary by document type and the model you use.

Compare at a glance

Build it yourself AI Data Foundry
Time to launch 3–12 months of development The day you sign up
Team required 2–5 AI engineers One business user
MS Office formats (DOCX · PPTX · XLSX) Separate extractors per format Native, high-fidelity support
Structure preservation (tables · formulas · reading order) Varies by extractor Accurate extraction, built on proven document technology
Automation pipeline Build and operate it yourself No-code workflows
Quality control Separate process Built-in web review (HITL)
Extensibility Custom development every time API · Webhook · MCP

Turn dormant documents
into data your AI can use

300 welcome credits · instant API key · see results right in your browser

Start for free