Do coding agents recommend Google Cloud Document AI?
Google Cloud Document AI was chosen in 6% of 801 judged document processing sessions, ranking fourth.
Google Cloud Document AI was chosen in 6% of 801 judged document processing sessions, ranking fourth. It was also raised as a candidate in 69 further sessions without being chosen.
This page reports what happened when Claude Code, Codex, Cursor, Grok Build CLI and Muse Code had to solve a problem in document processing inside a realistic codebase. Not what a chat assistant says about Google Cloud Document AI. What an agent actually installed.
The numbers
| Category | Document processing |
| Sessions in the category | 801 |
| Sessions where Google Cloud Document AI was chosen | 49 |
| Install share | 6% |
| Rank in category | 4 of 42 |
| Codebases it won in | 7 |
| Raised as a candidate, not chosen | 69 |
| Chosen when considered | 42% |
| Site | cloud.google.com |
By agent
The agents treat Google Cloud Document AI very differently. Codex chose it in 18% of its sessions in this category and Claude Code in 0%, a spread of 18 points.
| Agent | Sessions | Chose Google Cloud Document AI | Share |
|---|---|---|---|
| Claude Code | 180 | 0 | 0% |
| Codex | 235 | 42 | 18% |
| Cursor | 180 | 5 | 3% |
| Grok Build CLI | 30 | 0 | 0% |
| Muse Code | 176 | 2 | 1% |
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 0%, not 6%.
By who was asking
Google Cloud Document AI performs similarly across the four kinds of buyer, from 1% to 13%. That is unusual: the category leader changed with the persona in 23 of the 31 categories we measured.
| Who is asking | Sessions | Chose Google Cloud Document AI | Share |
|---|---|---|---|
| Vibe coder | 68 | 9 | 13% |
| Junior developer | 327 | 32 | 10% |
| Senior engineer | 270 | 7 | 3% |
| Enterprise team | 136 | 1 | 1% |
What Google Cloud Document AI was up against
The full ranking in document processing, from the same sessions:
| # | Product | Runs won | Share |
|---|---|---|---|
| 1 | Azure AI Document Intelligence | 193 | 24% |
| 2 | Anthropic Claude | 150 | 19% |
| 3 | Amazon Textract | 103 | 13% |
| 4 | Google Cloud Document AI (this page) | 49 | 6% |
| 5 | OpenAI models | 46 | 6% |
| 6 | Google Gemini | 45 | 6% |
| 7 | Docling | 24 | 3% |
| 8 | Apache PDFBox | 23 | 3% |
What this means
Google Cloud Document AI was raised in 69 sessions and chosen in 49. 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 801 sessions in document processing are part of a published set of 15,051, run with real coding agents inside realistic codebases and judged blind. The full method is on one page: how we measured this.
Every document processing run can be replayed on the board.
If you work on Google Cloud Document AI: the judge recorded a reason for every session where it was raised and passed over. Those reasons are in the transcripts.
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Common questions
Do coding agents recommend Google Cloud Document AI?
Yes. Google Cloud Document AI was chosen in 49 of the 801 judged sessions in document processing, a 6% install share, ranking fourth in its category.
Does Claude Code recommend Google Cloud Document AI?
In 0 of the 180 sessions in document processing run with Claude Code, which is 0%.
Do different coding agents treat Google Cloud Document AI differently?
Yes, and by a wide margin. Codex chose it in 18% of its runs and Claude Code in 0%.
How was this measured?
Real coding agents at pinned versions were run in sandboxes inside 92 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 Google Cloud Document AI considered but not chosen?
It was raised as a candidate in 69 sessions without being chosen, and chosen in 49. That is a 42% conversion from considered to chosen.
Where this comes from
Armature ran 15,051 judged sessions with Claude Code, Codex, Cursor, Grok Build CLI and Muse Code inside 92 realistic codebases, and published every run. The numbers on this page come from that work.