Security and privacy decision

Incogni

A capable developer can build a limited self-hosted opt-out runner (dozens of sites) using existing open-source projects, but reproducing Incogni's scale, continuous broker discovery, and verified removal volume is impractical for a lone developer.

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You pay

$7.99/mo

$96/yr

Read off the official pricing page.

You’d pay instead

$50one-off30 h to build

$50/mo8 h/mo upkeep

On cash alone, building overtakes the subscription at 7 seats.

Open-source builds that already do this

Every project below is open source and already does this job today. Fork one, self-host it, or take the parts you need - the build prompt further down assumes an empty file, and this is the shortcut past that. Licences differ; check the one on each card before you ship. All Incogni alternatives, with the arithmetic →

What a replacement has to do

  • Scan people-search/data-broker sites for a profile, submit opt-out/removal requests (forms/emails/DMCA), track request status and retry on schedule, store progress and send user reports.

What it still won’t have

  • Breadth and scale of coverage (Incogni: 420+ brokers / 2,420+ sites)
  • Ongoing site research and frequent additions of new brokers
  • Deloitte-verified removal volume and independent verification
  • 24/7 live support and money-back guarantee handled by vendor

What remains hard

  • Infrastructure at scale245M+ data removal requests completed, thanks to our automated service and privacy experts.
Read the build prompt

First-year cost

Keep paying

Paying is—cheaper in year one.

On cash alone, building overtakes the subscription at 7 seats.

Paid seatsseats

Money you would actually spend

Keep paying
—

Subscription price × seats × 12

Build it
—

AI build —APIs + hosting —

Time you would spend

—

—

What you would spend

What we assumed

The verdict above measures whether you could build it. This one is only about money.

Runnable build prompt

Not run yet
Build a self-hosted data-broker opt-out runner using Python (FastAPI) + Postgres + Redis for scheduling. Scope: scrape and match person profiles on a configurable list of 30 people-search/data-broker sites, generate and submit opt-out requests (form POSTs, scripted logins, and templated emails), record request status and retries, run recurring re-scans on a schedule, and provide a minimal React dashboard showing profiles, request history, and exportable monthly reports. Out of scope: attempting coverage parity with Incogni's 420+ brokers, enterprise Ironwall features, legal representation, and live phone support. Include error handling, retries, logging, and unit/integration tests for crawler, submitter, scheduler, and API endpoints.
How we checked4 sources · 3/3 runs agreed · evidence score 64

How the score was reached

  • Partly verdict base52
  • An open-source build was found+5
  • 4 cited sources+3
  • Price verified on pricing page+3
  • 3/3 assessment runs agreed+4
  • Hard moats found in the evidence-3
  • Evidence score64

The base comes from the verdict. Everything under it is a check that either happened or did not, and each one is a fact frozen in this record rather than a judgement made at render time - so the same evidence always produces the same number.

How scoring works →

Cited sources · 4

Every page the run actually retrieved.

Integrity checks

What held up, and what did not.

✓ Price read off the page✓ 3 independent runs, one answer✓ Citations limited to fetched pages! 1 moat quoted from the page