What is PhotoTag.ai?
PhotoTag.ai is a web-based AI tool that generates keywords, titles and descriptions for images and videos. It is built mainly for stock photographers and illustrators who must tag large batches before uploading to agencies.
You upload files, add optional context such as a location, and the AI returns metadata you can edit. Results export as a CSV for stock sites or as files with embedded IPTC, XMP or EXIF data. The service is live, though the company behind it publishes few details.
Key Features
- Batch tagging: PhotoTag.ai processes up to 1,500 files in one upload, according to reviews. Contributors can keyword a full shoot in one session instead of file by file.
- Titles and descriptions: The AI writes titles and descriptions alongside keyword lists for every file. Reviewers found the descriptions read naturally rather than like machine output, which saves rewriting before submission.
- Custom context: You can add a location, shoot details or priority keywords before processing. This context helps with the tool’s weak spot on landmarks and specific events.
- Keyword regeneration: Users can edit a description and regenerate keywords from it. This editing loop corrects misread scenes without uploading the file again, keeping credits and time spent on fixes low.
- Trending keywords: A trending keywords tab shows currently popular stock search terms. Contributors can add relevant trending terms to help files surface in agency searches and plan future shoots around demand.
- Lightroom plugin and API: A Lightroom Classic plugin tags photos without leaving your catalogue, and an API endpoint supports automated pipelines. Both keep metadata work inside existing workflows rather than a separate browser tab.
- Multilingual output: PhotoTag.ai generates metadata in more than 15 languages, including German, Spanish, Japanese and Simplified Chinese. Sellers on regional agencies can submit in local languages without a separate translation step.
- Wide format support: The tool handles JPEG, PNG, WEBP, TIFF and SVG images plus MP4, MOV and AVI video. Results export as CSV files or with embedded IPTC, XMP or EXIF data.
Pros
- Time saver: PhotoTag.ai cuts hours of manual keywording on large batches. Reviewers say the saved time goes back into shooting and editing, which matters for contributors uploading hundreds of files each week.
- Strong on still life: Reviewers rate output highly for product, still-life and landscape images. One tester scored still-life results at 8 to 9 out of 10, needing only light edits before upload.
- Stock-ready exports: CSV files suit Adobe Stock and Shutterstock uploads, and reviews mention compatibility with Magnolia and Storyblocks. Embedded metadata also travels with each exported file to other agencies.
- Vector and video support: SVG keywording sets it apart from photo-only taggers, according to Shotkit’s review. Contributors with mixed portfolios can tag photos, vectors and clips in one tool.
- Low per-file cost: Reported credit packs work out at about $0.004 to $0.009 per file, at one credit per file. Credits are reported not to expire, so occasional sellers avoid monthly commitments.
- Specific keywords: Reviewers found PhotoTag.ai suggestions specific enough to be useful rather than generic. Clear, single-subject images need little editing before submission, so simple batches move quickly from upload to agency.
Cons
- Uneven accuracy: Editorial and travel scenes often produce broader, less differentiated keywords. One tester averaged 7 out of 10 across ten mixed images, so complex shots need more manual work.
- Weak on context: The AI misses landmarks without a location hint and can overlook key details in complex scenes. Portraits and event shots need careful checking before upload to avoid misleading tags.
- Long descriptions: Generated descriptions often exceed the 200-character limit some stock agencies set. You may need to trim text before uploading, or the agency may reject or truncate the file’s description.
- Upload hangs: Reviewers report the web app hanging during uploads, and video processing takes much longer than images. Very large batches may need splitting into smaller uploads to avoid starting again.
- Variable translations: Non-English output quality varies and needs checking by a fluent speaker. Errors in another language can hurt discoverability on regional agencies, undoing the benefit of multilingual output.
- Sparse company info: Ownership, support details and pricing are hard to confirm before sign-up. The pricing page did not load for us, and a 2023 review described monthly plans instead.
Who is Using PhotoTag.ai?
- Microstock contributors: Tag large weekly batches for agencies.
- Vector illustrators: Keyword SVG files for stock sites.
- Videographers: Add metadata to stock footage clips.
- Photo archives: Organise and search large libraries.
Pricing
PhotoTag.ai reportedly uses pay-as-you-go credit packs, with one credit per file (checked October 2026, third-party reviews).
| Plan | Price | What you get |
|---|---|---|
| Free credits | Free | Small test allowance, reported |
| 2,000 credits | $18 | About $0.009 per file |
| 10,000 credits | $59 | About $0.006 per file |
| 50,000 credits | $190 | About $0.004 per file |
The pricing page did not load for us, and a 2023 review described monthly plans instead. Treat these figures as a guide and confirm them on the official checkout page.
What Makes PhotoTag.ai Unique?
Dedicated SVG and video keywording sets it apart from photo-only taggers, which matters for contributors who sell mixed portfolios. A Lightroom Classic plugin and an API let you keep tagging inside your existing workflow instead of juggling extra uploads.
Compatibilities and Integrations
- Platforms: Runs in any modern web browser.
- Adobe workflow: Lightroom Classic plugin for direct tagging.
- Developer access: API endpoint for automated pipelines.
- Export: CSV, plus IPTC, XMP and EXIF embedded files.
PhotoTag.ai Tutorials
A first batch takes only a few minutes.
- Create an account and use the free credits.
- Upload photos, vectors or videos.
- Add context such as location or subject.
- Review and edit the generated metadata.
- Export a CSV or tagged files for stock sites.
How We Rated It
| Criterion | Score | Why |
|---|---|---|
| Accuracy and Reliability | 3.6 | Weak on editorial scenes |
| Ease of Use | 4.4 | Simple upload and export |
| Functionality and Features | 4.0 | Video, vectors, many languages |
| Performance and Speed | 4.3 | Large batches process quickly |
| Customization and Flexibility | 3.9 | Context and keyword limits |
| Data Privacy and Security | 3.2 | Limited published privacy detail |
| Support and Resources | 3.1 | Sparse docs and support |
| Cost-Efficiency | 4.4 | Low per-file credit costs |
| Integration Capabilities | 4.0 | Lightroom plugin and API |
| Overall Score | 3.9 | Average of the nine criteria |
Summary
PhotoTag.ai suits stock contributors who need fast first-draft metadata for large batches. Its main weakness is uneven accuracy on editorial and travel scenes, so a human check remains essential. Always add location or subject context before processing, as this noticeably improves the keywords you get back.
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