Axia Extract vs Amazon Textract comes down to what you need back from the page. Textract wins on price for raw text at $0.0015 per page, while Axia costs half to a third of Textract's $0.07 structured-extraction bundle per page and returns your defined schema instead of generic key-value pairs you still have to map.
Every number in this comparison is real published pricing: AWS's public Textract pricing page, for standard US regions and the first 1 million pages a month, and Axia's live credit pricing, both checked August 2026. Both vendors revise pricing periodically, so re-check before budgeting.
| At a glance | Amazon Textract | Axia Extract |
|---|---|---|
| Raw OCR (text only) | $0.0015/page | Not the use case; every tier returns structured fields |
| Structured extraction | $0.01 to $0.07/page by API | $0.0056 to $0.0323/page (Small and Standard tiers) |
| Output shape | Generic key-value pairs, table cells, query answers | Your defined schema, nested fields included |
| Published accuracy | No per-field benchmark published | 98.2% average on SROIE2019, 99.9% on totals |
| Best for | Raw OCR, teams already deep in AWS | Schema-based extraction of invoices, receipts, IDs, forms |
That table is the summary. The rest of this Axia vs Textract comparison unpacks each row, because a per-page price only means something once you know what the page actually buys you.
Pricing: Textract's API menu against Axia's credit tiers
Textract isn't one price. It's a family of APIs billed separately, the gap between the cheapest and most expensive is more than 45x, and which endpoint you call decides everything about your bill.
That structure exists because each API does different work. Detect Document Text runs character recognition alone. Analyze Document groups those characters into forms, tables, or query answers, and Analyze Expense and Analyze ID add document-specific parsing on top. More reasoning per page means a higher price per page.
| Textract API | What it returns | Price per page |
|---|---|---|
| Detect Document Text | Raw characters, no structure | $0.0015 |
| Analyze Document, Tables | Table cells | $0.015 |
| Analyze Document, Signatures | Signature presence/location | $0.0035 |
| Analyze Expense | Receipt/invoice line items | $0.01 |
| Analyze ID | ID document fields | $0.025 |
| Analyze Document, Custom Queries | Answers to defined questions | $0.025 |
| Analyze Document, Forms | Key-value pairs | $0.05 |
| Analyze Document, Forms + Tables + Queries | All three combined | $0.07 |
| Analyze Lending | Loan document classification + extraction | $0.07 |
Axia prices in credits instead: 1 credit per page on the Small tier, for schemas of 10 or fewer flat fields, and 4 credits per page on Standard, with credits at ₱0.50 at entry volume down to ₱0.35 in bulk. At ₱62 to the dollar, a Standard page costs ₱2.00, or $0.0323, at entry pricing and ₱1.40, or $0.0226, in bulk.
Field-level bounding boxes are an optional add-on on Axia's side, not included above: 4 credits per page on top of the base rate, for teams that need to show reviewers exactly where a value came from on the page.
The head-to-head: like-for-like per page
The fair fight is structured extraction against structured extraction. That means Amazon Textract's $0.07 Forms + Tables + Queries bundle against Axia's Standard tier, and Analyze Expense or Analyze ID against Axia's Small tier, never Textract's $0.0015 raw-text rate against anything schema-shaped.
| Comparison | Textract | Axia (entry) | Axia (bulk) |
|---|---|---|---|
| Simple documents (Small vs Expense/ID) | $0.01 / $0.025 | $0.0081 | $0.0056 |
| Multi-field forms (Standard vs Forms+Tables+Queries) | $0.07 | $0.0323 | $0.0226 |
Standard lands under half of Textract's bundle at entry pricing and under a third in bulk. Small undercuts Analyze Expense ($0.01/page) before any volume discount and beats Analyze ID ($0.025/page) by a wide margin.
On the other side, quoting Textract's $0.0015 headline against any structured tool would be a mismatch, and we won't do it. Detect Document Text returns a wall of characters and coordinates: no fields, no schema, no idea which number is the invoice total. If searchable text is all you need, that rate is unbeatable, and our OCR comparison guide covers where raw extraction like that fits versus schema-based tools.
Output: generic key-value pairs vs your schema
Textract's Analyze Document response is generic. Forms mode gives you key-value pairs detected on the page, tables mode gives you cell grids, queries mode answers the questions you asked. None of it arrives asinvoice_total or vendor_name, so a developer still writes the mapping layer.
Axia's single call returns your defined schema directly, nested fields and all. Say you need vendor name, invoice number, line items, and a total: Textract's bundle means parsing three response shapes and writing logic to guess which key-value pair is the vendor name, while a schema-first API returns those four fields by name, every call.
That mapping layer is engineering time Textract's per-page price doesn't include, and it's the biggest hidden term in this comparison. Our guide to Axia's model tiers covers how schema shape decides which tier, and which price, you actually pay.
Accuracy: one side publishes numbers
Axia publishes field-level results on a public benchmark: 98.2% average accuracy across company name, address, date, and total fields on 347 real SROIE2019 receipts, with total amounts at 99.9%. Amazon doesn't publish comparable per-field numbers for Textract's generic output.
That doesn't make Textract inaccurate. It means you'll run your own evaluation to find out, while Axia has already put a number next to the claim, one you can check against the published methodology before signing up.
When each one wins
Pick Textract if your team is already deep in AWS, with IAM roles and Lambda triggers built around it. Switching carries a real migration cost that a lower per-page price won't automatically offset, and keeping everything inside one cloud account has operational value of its own.
Textract also wins outright for pure OCR with no downstream schema need, like indexing scanned archives for full-text search. Its free tier helps too: new AWS customers get three months of free pages, 1,000 a month for Detect Document Text and 100 for most Analyze Document features, which makes a proof of concept effectively free.
Pick Axia Extract for the invoices, receipts, IDs, and forms most teams are actually trying to automate. Across the structured tiers compared above it costs less per page, skips the response-mapping step entirely, and backs its accuracy with a published per-field number instead of an unverified claim.
Whichever way you lean, multiply the per-page figure by your real monthly volume before committing. At a few hundred pages a month the Axia vs Textract gap is grocery money. At tens of thousands of pages it becomes a line item finance asks about every quarter, and that's before counting the mapping code Textract leaves you to write and maintain.