Security and privacy decision

DeleteMe

A technical user can build a narrow self-service portal and automation to assist opt-outs, but reproducing DeleteMe’s scale, coverage, and human-run removal operations (the product’s durable value) is impractical for a small DIY project.

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Subscription$10.75/month
Initial build80 hours
Monthly upkeep12 hours + $0
Evidence3/3 runs agree

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.

What a replacement has to do

  • Collect user identity, discover listings on data-broker sites, generate and submit opt-out/removal requests, track status and produce quarterly reports

What it still won’t have

  • Coverage and scale of listings removed (DeleteMe claims wide coverage built over years)
  • Experienced privacy experts and manual removal labor
  • Trust signals, brand reputation, and guaranteed SLA/guarantee
  • Ongoing manual operations to handle anti-bot measures and changing removal workflows

What remains hard

  • Brand trustWith over 100 Million personal listings removed since 2010, DeleteMe is the most trusted and proven privacy solution available.
  • Brand trustA+ BBB Rating Trusted Service
Read the build prompt

First-year cost

Keep paying

Paying ischeaper in year one.

On cash alone, building overtakes the subscription at 1 seat.

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 minimal self-hosted privacy-removal assistant using Node.js + Express, Next.js frontend, PostgreSQL, Redis for queues, and a worker pool. Include: (1) signup and Stripe payment for yearly plans (one seat), (2) account profile pages to collect names/addresses/aliases, (3) a crawler/lookup worker that runs search queries and scrapes a configurable list of data-broker pages, (4) an opt-out request generator that prepares site-specific removal requests and enqueues manual tasks if automation fails, (5) a reviewer UI to process manual removals and mark success, (6) a scheduler to re-scan accounts quarterly and send PDF/email reports. Out of scope: large-scale distributed scraping across thousands of brokers, litigation or legal takedown services, training proprietary ML models. Include basic error handling, retries for failed submissions, rate-limiting, logging, and unit/integration tests for core flows.
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
  • 3/3 assessment runs agreed+4
  • 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 not confirmed on the page — this pricing page renders its price in the browser✓ 3 independent runs, one answer✓ Citations limited to fetched pages! 2 moats quoted from the page