# Do coding agents recommend Amazon Textract? > Amazon Textract was chosen in 10% of 360 judged document processing sessions, ranking third. Measured with Claude Code, Codex and Cursor. Source: https://armature.tech/library/do-coding-agents-recommend-amazon-textract Published: 2026-09-15 Publisher: Armature, Inc. (https://armature.tech) --- > Amazon Textract was chosen in 10% of 360 judged document processing sessions, ranking third. It was also raised as a candidate in 83 further sessions without being chosen. This page reports what happened when Claude Code, Codex and Cursor had to solve a problem in document processing inside a realistic codebase. Not what a chat assistant says about Amazon Textract. What an agent actually installed. ## The numbers | | | | --- | --- | | Category | Document processing | | Sessions in the category | 360 | | Sessions where Amazon Textract was chosen | 37 | | Install share | 10% | | Rank in category | 3 of 30 | | Codebases it won in | 7 | | Raised as a candidate, not chosen | 83 | | Chosen when considered | 31% | | Site | aws.amazon.com | ## By agent The three agents treat Amazon Textract very differently. Codex chose it in 18% of its sessions in this category and Claude Code in 3%, a spread of 15 points. | Agent | Sessions | Chose Amazon Textract | Share | | --- | --- | --- | --- | | Claude Code | 120 | 3 | 3% | | Codex | 120 | 22 | 18% | | Cursor | 120 | 12 | 10% | A single blended install share would report the midpoint and hide both ends. If most of your users run Claude Code, your real position here is 3%, not 10%. ## By who was asking Amazon Textract does much better with one kind of buyer than another. It won 23% of sessions asked as enterprise team and 3% of those asked as vibe coder. | Who is asking | Sessions | Chose Amazon Textract | Share | | --- | --- | --- | --- | | Vibe coder | 30 | 1 | 3% | | Junior developer | 180 | 23 | 13% | | Senior engineer | 120 | 6 | 5% | | Enterprise team | 30 | 7 | 23% | ## What Amazon Textract was up against The full ranking in document processing, from the same sessions: | # | Product | Runs won | Share | | --- | --- | --- | --- | | 1 | Anthropic Claude | 87 | 24% | | 2 | Azure AI Document Intelligence | 76 | 21% | | 3 | Amazon Textract **(this page)** | 37 | 10% | | 4 | Google Cloud Document AI | 31 | 9% | | 5 | Google Gemini | 17 | 5% | | 6 | Ocrolus | 15 | 4% | | 7 | Reducto | 13 | 4% | | 8 | Azure AI Content Understanding | 11 | 3% | ## What this means Amazon Textract was raised in 83 sessions and chosen in 37. That ratio is balanced enough that the ceiling is presence rather than integration: the product converts reasonably when it is on the table, and it is not on the table often enough. ## Where these numbers come from The 360 sessions in document processing are part of a published set of 7,673, run with real coding agents inside realistic codebases and judged blind. The full method is on one page: [how we measured this](/library/how-we-measured-this). Every document processing run can be replayed on [the board](/leaderboards/document-processing). If you work on Amazon Textract: the judge recorded a reason for every session where it was raised and passed over. Those reasons are in the transcripts. ## Common questions ### Do coding agents recommend Amazon Textract? Yes. Amazon Textract was chosen in 37 of the 360 judged sessions in document processing, a 10% install share, ranking third in its category. ### Does Claude Code recommend Amazon Textract? In 3 of the 120 sessions in document processing run with Claude Code, which is 3%. ### Do different coding agents treat Amazon Textract differently? Yes, and by a wide margin. Codex chose it in 18% of its runs and Claude Code in 3%. ### How was this measured? Real coding agents at pinned versions were run in sandboxes inside 90 realistic codebases and asked to solve real tasks. A simulated project owner approved or questioned each recommendation before any code was written, and a judge from a model family that builds none of the agents read every session blind. ### How often is Amazon Textract considered but not chosen? It was raised as a candidate in 83 sessions without being chosen, and chosen in 37. That is a 31% conversion from considered to chosen. ## Read next - [How to get picked for document processing by coding agents](https://armature.tech/library/document-processing-coding-agents-playbook) (Markdown: https://armature.tech/library/document-processing-coding-agents-playbook.md) - [Do coding agents recommend Anthropic Claude?](https://armature.tech/library/do-coding-agents-recommend-anthropic-claude) (Markdown: https://armature.tech/library/do-coding-agents-recommend-anthropic-claude.md) - [Do coding agents recommend Azure AI Document Intelligence?](https://armature.tech/library/do-coding-agents-recommend-azure-ai-document-intelligence) (Markdown: https://armature.tech/library/do-coding-agents-recommend-azure-ai-document-intelligence.md) - [Do Claude Code, Codex and Cursor pick the same tools?](https://armature.tech/library/do-claude-code-and-codex-agree) (Markdown: https://armature.tech/library/do-claude-code-and-codex-agree.md) --- Armature helps software products get discovered and used by coding agents. Service: https://armature.tech/discoverability · Results: https://armature.tech/leaderboards/sectors · Contact: contact@armature.tech