Verified cases

The moment a toy was pointed at work

Open the real page ↗headshotpro.com · alive as of 2026-08-31

AI-generated professional headshots. The lesson is not the model; it is the reframing — the same generation, moved from novelty avatars to photos people need for job applications and company profiles, became a business. ⚠️ Early claims are relatively consistent across write-ups, but the larger revenue claims have no independent verification. We publish neither (grade B).

In plain words

Upload a few photos, get portraits you could put on a CV or a company page. It started as novelty avatars; aimed at work, people paid.

The whole thing at a glance

  1. To whom

    Job seekers and employees ne…

  2. What

    AI SaaS

  3. Found how

    X — the founder's public wor…

  4. Paid how

    Per-package purchases of gen…

Flow: To whom, then What, then Found how, then Paid how

Founder
Danny Postma
Country
NL
Team
Startup cost
To first revenue
Automation
high
Reported revenue
Revenue not disclosed

What is sold

Per-package purchases of generated images

Pricing is published on the official site (liveness confirmed 2026-08-31). ⚠️ We do not copy the amounts across.

Who buys

Job seekers and employees needing CV, company or profile photos; team orders

What arrives is not what you keep

  1. What the customer paidThe number on the invoice
  2. AI toolsA share of the monthly subscription
  3. Platform feeDiffers by platform
  4. TaxDiffers by country and business form
  5. What is leftAt or below zero, it is not a price
The rows are not scaled to amounts. Tools, fees, and tax differ per person, so we do not draw a share we did not measure — put your own numbers in the calculator.

This case does not publish its own tool costs, fees or tax. So we show the order and the items only — put your own numbers into the calculator.

AI's part and the person's part

Already had

Someone who had shipped products before, with an audience built in public. Not a from-scratch start.

If this is large, the AI is not the reason

What the AI did

A personalised model is trained from user photos and generates portraits. Several services shared this capability at the same time — the difference came from defining which photo was being made.

the part a tool replaced

What the person did

Re-deciding the use case. The same generation makes a fun avatar or an interview photo; only one of those has a price attached. The human work was not improving the model but choosing a situation where money was already being spent.

stories that omit this do not replicate

The three columns are not proportional to contribution — we did not measure that. This is a schematic for separating them.

How customers were found

  1. X — the founder's public work

  2. Search traffic

  3. Affiliate programme

  4. Launch exposure on product discovery platforms

  5. Paying customers

    Pricing is published on the official sit…

Channels we could confirm from public sources. Conversion rates were not disclosed, so they are not shown.

Flow: X — the founder's public work, then Search traffic, then Affiliate programme, then Launch exposure on product discovery platforms, then Paying customers

How we verified this

Evidence strengthB· 2 source(s)

Public dashboard or platform figure. May be self-reported

Confirmed — the service is live (official site HTTP 200, 2026-08-31), the founder is named, and the cited write-up is live (HTTP 200). Not confirmed — revenue. Per the material we were given, the early claims are relatively consistent across sources, while the larger monthly claims lack independent verification. 🔴 When one case mixes a plausible claim with an unverified one, the common error is letting the first vouch for the second. We publish neither figure. The grade turns on who confirmed a number, not on how plausible it sounds.

See the grading rules

What made it work

The same capability is free when attached to fun and priced when attached to work. Plenty of free users and no buyers is usually a signal to move the use case, not to add features. Choosing a situation where money is already being spent is the most reliable way to raise conversion.

Risks

  • Low barriers mean copies arrive fast, and several similar services appeared in the same period.
  • Likeness and consent are a standing risk.
  • The larger revenue claims are unverified — do not build an earnings expectation on this case.

Does this work in Korea?

Demand is, if anything, clearer in Korea — CV and ID photographs already carry set prices and studio visits are routine. ⚠️ Which means the competitor is the local photo studio, not another AI service. The deciding factor is not price but whether the output is accepted as a real submission — miss the size, background or dress requirements and cheap does not sell. ⚠️ Face data means consent, retention and deletion come first.

Replicability in Korea3/5
Difficulty3/5

Solo-feasible: yes · Automation: high

7-day action plan

  1. Step 1. Find and write down the actual format requirements for CV and ID photos in your market

  2. Step 2. Test with five outputs whether generated images meet those requirements

  3. Step 3. Survey three local studios and record their prices

30-day action plan

  1. Step 1. Add a checking step that only releases outputs meeting the format rules

  2. Step 2. Produce photos free for five job seekers and confirm whether they actually submitted them

  3. Step 3. Price it only after outputs are being used in real submissions

Run the numbers

We do not print a single projected figure here. Put your own numbers in instead.

Break-even calculator →

Get the next verification result

We check the AI income stories people are talking about, grade the evidence, and send you what we found — including what we could not confirm.

Words you may not know

Verification grade
How far we checked this case. A means the revenue was confirmed by someone other than the founder; B means the business exists but the revenue is only the founder's word.
Revenue
Everything that came in. Tools, fees and tax still have to come out before it is what you keep. The two are not the same.
MRR
Money that arrives every month, as opposed to a one-time payment.
Self-reported
A number the person stated about themselves. Nobody else confirmed it, which is why we do not print those numbers.
Replicability
How likely someone else is to get a similar result. The more the founder already knew the field, the harder it is to copy.