infratex
/ THE END-TO-END DATA PIPELINE

The end-to-enddata pipelinefor agentic AI.

Infratex turns raw PDFs and ordered image batches into production-ready context for agents — parse, index, search, and generate cited answers through one coherent pipeline.

View pipeline→Read the docs
quarterly_report.pdfp. 14
Operating Performance · 2024
paragraph
Period
Revenue
YoY
Tier
Q1
12.4M
+18%
A
Q2
14.1M
+14%
A
Q3
13.8M
−02%
B
Q4
17.2M
+25%
A+
table · 5×4
Rt = Σpi · qi1 − εi(3.4)
equation · latex
Q1Q2Q3Q4Fig. 3 · revenue (M)
chart · bar
structured · jsonl● live
paragraphp.14 · b1
"Operating revenue grew by 18% in Q1, led by enterprise contracts and a strengthened…"
table · 5×4p.14 · b2
{ rows: [
{ "period": "Q1", "rev": 12.4, "yoy": 0.18, "tier": "A" },
… 3 more
] }
equation · latexp.14 · b3
R_t = \sum \frac{p_i \cdot q_i}{1 - \varepsilon_i}
chart · barp.14 · b4
{ kind: "bar", x: ["Q1","Q2","Q3","Q4"],
y: [12.4, 14.1, 13.8, 17.2],
unit: "M_USD" }
structure preserved · 100%4 / 4 blocks
/ 01

Knowledge work lives in documents.

Helping agents work through them takes data that captures the long tail of real-world complexity — not just clean PDFs, but the messy, mixed-modal context production runs on.

/ 02

We model documents from first principles.

Layout, reading order, tables, formulas, citations — every artefact your agent will reason over is parsed into typed, queryable structures with explicit provenance back to the page.

pdfblockspanentityciteschemas your agent can reason over
/ 03

And refine relentlessly with your traffic.

Schemas, indexes, and retrieval recipes improve continuously after deploy — validated through evals, expanded with edge cases, and tuned against the queries your agents actually run.

refineschema_v3.json
/ PIPELINE

Four stages.
One contract.

Parse, index, search, and generate share a single schema. Switch on what you need; the contract between stages doesn't change.

document understanding

Parsing

Setting the gold standard for real-world parsing. End-to-end coverage of layout, reading order, 50+ language OCR, table-to-HTML, forms, formulas, chart-to-mermaid, and more — every artefact emitted with span-level provenance back to the page.

STAGE 01 · SAMPLE
{"type": "section_h2","text": "Schedule A..","page": 12,"bbox": [72, 144, 412, 168],"order": 47,"lang": "en",}
20K+
Schemas
3M+
Elements
50+
Languages
21
Domains
/ PRODUCT

A complete, living data product.

We identify high-value capabilities, benchmark where models fall short, and craft the data that closes the gap — validated through evals and continuous iteration.

01

One pipeline

Parse, index, search, and generate stay aligned end-to-end. Schema changes flow through automatically — no glue code, no drift between stages.

02

Typed schemas

Every emitted artefact — block, span, entity, citation — carries an explicit type with span-level provenance back to the page. Agents reason over data, not strings.

03

Insights

Traces, eval dashboards, and distribution drift detection ship with the pipeline. See exactly where your agents fail, and why, before users do.

04

Iterative

Quality, coverage, and recall improve continuously after delivery. Continuous evals, edge-case mining, and a direct line to our team.

/ HOW WE WORK

From first call to production in days.

Pilots ship in under two weeks. Full rollout depends on your eval bar — not our pipeline.

Talk to us→
01

Tell us your use-case

A short call to understand your sources, agents, and the answers you need to ground. We onboard your team onto the platform and connect your first corpus.

02

Configure the pipeline

Pick parsing schemas, index recipes, and retrieval contracts that match your domain. Sample everything in the inspector before a single run hits production.

03

Eval & deploy

Continuous evals against representative queries. Ship to a staged endpoint, watch traces in real time, then promote when the numbers hold.

04

Improve forever

Schemas, recall, and grounding quality keep improving with traffic. Edge cases get mined, datasets get expanded, your team gets direct access to ours.

/ FROM THE TEAMS SHIPPING ON IT
“

Infratex collapsed three brittle stages into one contract. Our agent finally stops fabricating page numbers.

Eng lead · Series-B legal AI
“

The eval loop is the unlock. We see drift on a Wednesday and have a fix shipping by Friday.

ML platform · public fintech
“

We replaced four vendors. Parse-quality alone made the call; the indexing and citations were a bonus.

Founding eng · clinical-trial copilot
/ FAQ

Questions, before the call.

Anything missing? Email hello@infratex.ai.

Infrastructure. We don't train or sell foundation models — we produce the pipeline (parse, index, search, generate) and the data contracts that sit between your documents and whatever model you're running.