AI Data Extraction Services: Beat $0.05 a Page in 2026?

The most useful thing a cost guide in this category can tell you is that two of the three hyperscalers will not quote you a per-page price. AI data extraction services are engagements — not licences — in which a provider builds and operates the pipeline that turns invoices, claims, statements, or contracts into structured fields your systems can read, and prices the work by document class and exception rate rather than by the page.

TL;DR: the API layer underneath is cheap and published — Amazon charges $0.0015 a page for plain text extraction. The integration, exception handling, and validation layer on top is where the money goes, and no vendor publishes a number for it.

That gap is not a marketing dodge. It reflects a real measurement problem: a clean typed invoice and a scanned handwritten bill of lading cost wildly different amounts to process correctly, and no single per-page figure describes both. Every price in this guide was refetched on July 28, 2026, on two separate reads, at standard published rates with no promotional or negotiated discount applied. Where a vendor publishes nothing, this guide says "contact vendor" rather than estimating.

Key Takeaways

• Microsoft publishes a hard free tier — 0 to 500 pages a month — but rendered every one of its per-1,000-page rate cells as a $- placeholder at read time, alongside a disclaimer that prices are estimates only.

• Amazon publishes real per-page rates: $0.0015 a page for plain text detection, $0.05 a page for form extraction, and $0.070 a page for forms, tables, and queries combined on the first million pages.

• Google Cloud's Document AI overview documents six processor types and attaches no accuracy percentage, page limit, or throughput figure to any of them — so accuracy cannot be priced from hyperscaler documentation.

• Vendor case-study figures are real but are not category averages: Rossum reports 90% accuracy after 10 documents at the Port of Rotterdam, which is that customer's result, not a benchmark you should budget against.

• Decision rule: if your documents are one template and already digital, buy the API and stop — a services engagement is overhead you do not need at that variance level.

• Decision rule: the number to negotiate is exception rate, not price per page. A 4% exception rate on a high-touch document class costs more in review labour than the entire extraction bill.

What the Platform Vendors Actually Publish

Start with the vendor most buyers price first, because the result is instructive. According to Microsoft's Azure AI Document Intelligence pricing page, the free tier covers 0 to 500 pages free per month across all document types on both the web and container deployments — a genuinely useful number for a pilot. Past that tier, the page is far less helpful than it looks.

Azure's published free tier: 0 to 500 pages per month. Everything above it is a conversation. According to Microsoft's own pricing page, every per-1,000-page rate cell — Read, prebuilt models, custom classification, custom extraction, custom generative extraction, query fields, and each batch variant — rendered as $- at read time, with commitment-tier monthly fees and overage rates showing the same placeholder. The page states plainly that "Prices are estimates only and are not intended as actual price quotes," and directs buyers to sign in to the Azure pricing calculator.

Google withholds a different category of number. According to Google Cloud's Document AI documentation overview, 6 named processor types are documented — Enterprise Document OCR, Form Parser, Layout Parser, Custom Extractor, Custom Classifier, and Custom Splitter, plus up-trainable pretrained processors — with no accuracy percentage, page limit, throughput figure, or price attached to any of them.

Read that table as a buying signal rather than a complaint. Two of four vendors will not give you a rate card without a sales conversation, which means any "average cost per page" figure you find elsewhere was either modelled, negotiated under an agreement you cannot see, or invented.

The Per-Page Rates You Can Actually Verify

Amazon is the exception, and it is the right anchor for a build-versus-buy comparison. AWS describes the product on its Textract product page as a way to "Automatically extract printed text, handwriting, layout elements, and data from any document" — that page itself carries no numbers, but the pricing page does.

According to AWS's Textract pricing page, Detect Document Text runs $0.0015 per page for the first 1 million pages and $0.0006 per page beyond it, in the US West (Oregon) region the page quotes. The feature-level rates climb sharply from there, which is the detail that reshapes most buyers' cost models.

The spread matters more than any single cell. Plain text detection and full form-plus-table extraction differ by more than 46 times per page, so a cost model built on the OCR rate understates a structured-extraction workload badly. Free tiers differ in the same direction, and according to AWS, the free allowance is 1,000 pages a month for Detect Document Text over three months but only 100 pages a month for Forms, Tables, and Layout.

Four Cost Drivers That Move Your Real Number

Per-page API rates are the smallest line in most extraction budgets. The four drivers below are what a provider is actually quoting when they refuse to give you a single number, and they are the four things to measure before you take any quote seriously.

Exception rate is the one buyers consistently underweight. A pipeline that extracts 96% of documents cleanly still routes the remaining 4% to a person, and at meaningful volume that queue — not the per-page rate — sets your monthly cost. That is why any honest provider asks for a document sample before quoting, and why this guide will not publish a headline cost per document.

Governance belongs in the same budget line. According to NIST, the AI Risk Management Framework released on January 26, 2023 organises AI risk work into four functions — Govern, Map, Measure, and Manage — and the Measure and Manage functions are precisely the ongoing work a managed engagement absorbs and a raw API does not.

What Vendors' Own Customer Numbers Do and Don't Prove

Specialist platforms publish outcomes where hyperscalers publish silence, and those outcomes are worth reading — as long as you read them as single-customer results. According to Rossum's published customer results, the Port of Rotterdam reached 90% accuracy after 10 documents, a figure Rossum attributes to that customer specifically rather than to the platform generally.

According to Rossum, Fugro moved invoice processing from 2 minutes to 35 seconds per document across 300,000 invoices annually — Rossum reports Fugro at 35 seconds per invoice, down from 2 minutes. Treat that as evidence the ceiling is high for a well-scoped AP workload, not as a number to put in your own business case. Rossum publishes no pricing, so the cost side of every one of those outcomes is a contact-vendor conversation.

Buying the Engagement Instead of the API

Here is where the arithmetic gets concrete. A 40-person freight brokerage pushing 6,400 supplier invoices a month through Textract's Forms feature pays $0.05 a page at AWS's published rate — 6,400 × $0.05 = $320 a month for extraction. Wire the same volume as a workflow instead and the shape changes: an s3:ObjectCreated:Put event fires when the invoice lands, analyze_document runs with the forms and tables feature types, low-confidence fields route to a reviewer queue rather than into the ledger, and the approved record writes to the accounting system.

US Tech Automations builds that trigger-to-write-back path, so the $320 API line holds steady while the reviewer queue — the part that actually scales with headcount — is what shrinks.

The second half of the engagement is the unglamorous part. US Tech Automations runs the retry and reconciliation layer around those calls: a failed write-back is re-queued rather than dropped, every extracted field carries its confidence score and source page for audit, and a document class that starts drifting raises a flag instead of quietly degrading. That is the layer the data extraction agent surface exists to run, and it is the reason the comparison a services buyer needs is API-plus-integration-labour versus a managed engagement — never API price alone.

Our own delivery-capacity numbers come from an adjacent pipeline and are worth stating plainly for that reason. In our publishing pipeline we measured roughly 3,200 pages shipped in two weeks, against an internal operating estimate — not an artifact-backed measurement — of about 1,000 pages a month of downstream indexation capacity. The transferable lesson for an extraction buyer is that the processing step was never the ceiling; the step after it was. Every page we ship, including this one, clears a fail-closed automated content gate first.

For teams already partway down this road, data entry automation for small business covers the pre-extraction groundwork, and business data entry automation walks the write-back side in more detail.

Where a Services Engagement Is the Wrong Purchase

When not to use US Tech Automations, stated plainly: if your documents are a single stable template arriving as clean digital PDFs, buy Textract or Document AI directly and write 200 lines of glue code — an engagement adds cost without adding accuracy. If you process fewer than 500 pages a month, Azure's free tier covers you outright and paying anyone is premature. And if your bottleneck is that nobody has decided which fields matter, that is a process problem no vendor can extract you out of.

Most readers' real alternative is not "do nothing" — it is stitching Textract to a spreadsheet through Zapier, Make, or n8n. That works until it doesn't. At 6,400 invoices a month a per-task pricing model gets expensive fast, and none of those tools give you a retry with backoff when the ERP write fails mid-batch, a confidence threshold that routes a doubtful field to a human, or an audit trail linking a posted amount back to the pixel it came from.

US Tech Automations supplies exactly those three things — orchestration, error handling, human-in-the-loop review — which is the difference between a demo and a pipeline finance will sign off on.

Our own buy-side extraction queries: 136 impressions, 0 clicks. Across seven explicitly buy-side extraction queries on our own property between January 1 and May 20, 2026, our Search Console harvest recorded 136 impressions and zero clicks, with "ai powered data extraction company" already averaging position 12.7 and "ai data extraction company" at 28.7. Buyers in this category are finding pages and bouncing at the result, which is a fair signal that most pages here answer the wrong question — cheapest per page, rather than what changes your exception rate.

Is This Guide for You?

This is written for operations and finance leads at firms processing somewhere between roughly 2,000 and 100,000 documents a month across more than one layout, with a system of record — an ERP, a TMS, an accounting platform — that the extracted data has to land in cleanly. If you already know your monthly page volume and your current manual review hours, you have everything needed to evaluate a quote from any vendor on this page.

Red flags: Skip an engagement entirely if you process under 500 pages a month, if every document is one unchanging digital template, or if no one has yet defined which fields must be captured and validated — in those three cases the direct API, the free tier, and an internal decision respectively are the right next step, and a services conversation is premature.

If you also need the surrounding workflow rather than just the extraction step, business workflow automation compared sets the extraction decision inside the wider stack.

Frequently Asked Questions

How much do AI data extraction services cost per page?

No vendor on this page publishes a per-page services rate, and this guide will not estimate one. The verifiable per-page numbers are API rates only: $0.0015 a page for Textract's text detection and $0.05 a page for its forms extraction, per AWS's published US West (Oregon) pricing checked July 28, 2026. Services pricing is quoted against document class, variance, and exception rate — ask any provider for a written quote after they review a document sample.

Why does Azure show $- instead of prices?

Because the rate table on Microsoft's pricing page renders placeholder values and the page states that prices are estimates only, not actual quotes, directing buyers to the Azure pricing calculator instead. The one hard number Microsoft does publish there is the free tier of 0 to 500 pages per month. Anyone quoting you an Azure Document Intelligence per-page rate got it from a calculator session or an agreement, not from the public page.

Is Amazon Textract cheaper than hiring an extraction provider?

On the API line, always — $0.05 a page for forms extraction is far below any managed rate. That comparison is incomplete, though, because it prices the extraction call and nothing else: not the integration to your system of record, not the reviewer queue for low-confidence fields, and not the on-call burden when a write-back fails. Price API-plus-integration-labour against the engagement, not API against engagement.

Which vendor publishes accuracy benchmarks?

None of the hyperscalers do. Google Cloud's Document AI overview documents six processor types with no accuracy percentage attached to any of them, and neither Microsoft's nor Amazon's pages carry accuracy claims either. The only accuracy figures available are vendor case studies tied to named customers, such as Rossum's 90%-after-10-documents result at the Port of Rotterdam — a specific customer's outcome, not a benchmark.

What should I ask for in a proposal?

Four things, in this order: the number of distinct document classes in scope, the assumed exception rate and who pays for review time above it, the write-back target system and who owns failures there, and the per-class accuracy threshold the provider will be measured against. A proposal that leads with a page price and skips exception rate has priced the cheap part of the problem.

Can I start on a free tier and migrate later?

Yes, and it is the sensible sequence. Azure's 0-to-500-pages-a-month free tier and Textract's 1,000 free Detect Document Text pages a month for three months are both sufficient to test whether your documents extract cleanly at all. Run 200 real documents through before anyone quotes you, because the exception rate that emerges is the single figure that determines what an engagement should cost.

Does volume discounting actually help?

Somewhat, and only on the API line. Textract's rates step down above one million pages — text detection from $0.0015 to $0.0006 a page, forms-plus-tables-plus-queries from $0.070 to $0.055 — and Azure publishes commitment tiers, though with placeholder amounts. Neither discount touches review labour, which is why a high-variance workload can get more expensive per document as volume grows.

Sources and Further Reading

Every figure above was read directly from the primary source on July 28, 2026, on two separate reads each, at standard published rates:

Two vendor prices were deliberately left out of this guide because they could not be substantiated: no per-page services rate appears anywhere here, and no Azure per-1,000-page rate is quoted, because the public page did not display one on either read.

The pattern across all five sources is consistent. The cheap, published part of this category is the extraction call; the expensive, unpublished part is everything that happens to a field after it is extracted. Price the second part or you have not priced the project. When you are ready to compare a managed engagement against your current API-plus-labour arrangement, the plans and what each includes are listed at ustechautomations.com/pricing.