PhotoMentor API
Structured photo critique for products that need more than a generic caption
Upload a photo. Get a score, genre, verdict, full critique, strengths, weaknesses, and three advice variants. Built for schools, contests, and photo platforms that need consistent photography feedback inside their own workflow.
Access is provisioned per client. Keys, quotas, and onboarding are handled directly by our team.
{
"request_id": "9e3f7b62-...",
"score": 7.2,
"genre": "Street Photography",
"verdict": "Strong timing, weak edge control.",
"critique": "The frame has energy, but...",
"strengths": ["Timing", "Subject separation"],
"weaknesses": ["Edge tension", "Flat light"],
"advice": {
"purist": "Step left and simplify the frame.",
"standard": "Reframe to clean the right edge.",
"creative": "Lean harder into the diagonal tension."
},
"visual_facts": "One person crossing a street...",
"mood": "restless"
}Where it fits
The API is not positioned as a generic image captioner. It is designed for products that need photography-specific judgment, structured output, and predictable integration.
Photography schools
Use it for assignment review, critique queues, and asynchronous coaching. Students get immediate structured feedback before an instructor steps in.
Contests & portfolio reviews
Add a first-pass critique layer, pre-screen submissions, or provide entrants with objective analysis alongside human judging.
Photo products & communities
Embed scoring, critique, and coaching into portfolio tools, challenge platforms, or creator products without building a critique engine from scratch.
Custom mentor profiles for schools and branded programs
The API can also be deployed with a custom mentor layer tailored to a specific teacher, reviewer, or educational program. That means the critique can be aligned not only structurally, but stylistically: vocabulary, tone, emphasis, and teaching priorities.
This is already working internally with the Artyom Chernov mentor profile. For some clients, the same approach can extend beyond text into voice delivery, so critique feels closer to a named instructor rather than a generic assistant.
Managed Customization
- Text persona: tone, phrasing, and pedagogical style aligned to a specific mentor.
- Curriculum bias: emphasize the criteria that matter to a school, contest, or review workflow.
- Voice layer: optional spoken delivery for selected mentor profiles.
- Provisioning model: configured per client, not exposed as a public request parameter in v1.
What the API returns
- Score: overall 0–10 rating with one decimal
- Genre: automatically inferred photography genre
- Verdict + critique: short hard truth and full analysis
- Strengths / weaknesses: structured lists ready for UI cards
- Advice modes: purist, standard, and creative guidance
- Visual facts + mood: useful for rendering richer review experiences
Operational contract
- Auth: `X-API-Key` header
- Request format: multipart upload, one image per request
- Supported files: JPEG, PNG, WebP, GIF up to 20 MB
- Languages: English, Russian, German, Spanish
- Tone modes: brutal or supportive
- Rate limits: per-client hourly and daily quotas, plus IP-level abuse brake
How access works
The API is provisioned per client. There is no public self-serve key generator yet. Access is issued manually so quotas, use case, and rollout can be matched to a real integration.
1
Talk to us
Tell us your use case, expected volume, and timeline.
2
We provision your key
We create a client key, alias, and quota bucket for your account.
3
Key is delivered once
You receive the raw key securely. Only its hash is stored on our side.
4
Use it in X-API-Key
Your integration sends the key in the `X-API-Key` header on every request.
Documentation
Bring the API into a real integration path
The technical docs include auth, request format, error contract, `curl` / Python / JavaScript examples, and the downloadable OpenAPI spec.