Security and privacy decision

Optery

A capable developer can build a narrow self-hosted workflow for scanning a subset of sites and automated opt-outs, but Optery’s patented search technology, SOC 2 certification, broad site coverage, and human-assisted removal workflows are durable advantages that make a full replacement impractical for a single builder.

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Subscription$3.99/month ✓ verified
Initial build80 hours
Monthly upkeep20 hours + $150
Evidence3/3 runs agree

No open-source build does this yet

Nothing published replaces this one, so a replacement starts from an empty file. Here is what it would have to cover.

What a replacement has to do

  • Automated discovery of profiles on people-search/data-broker sites and submission of opt-out/removal requests with progress tracking and periodic re-scans.

What it still won’t have

  • coverage breadth of 635+ sites and ongoing additions
  • patented search and automated opt-out technology
  • SOC 2 Type II certification and associated controls
  • assigned human Privacy Agents and “Humans + Machines” workflows
  • built-in screenshot verification and removal reports

What remains hard

  • Proprietary modelsOptery has two United States Patents for search technology enabling us to find and remove more customer profiles than any other company.
  • Compliance and regulationOptery completed its AICPA SOC 2, Type II security certification by Prescient Assurance.
Read the build prompt

First-year cost

Keep paying

Paying ischeaper in year one.

On cash alone, building overtakes the subscription at 40 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 minimal self-hosted data-removal service using Node.js (Express), Postgres, Puppeteer, Redis for scheduling, and a small React dashboard. Core features in scope: 1) run a Google/Bing-based profile discovery job that records candidate profiles and captures screenshots; 2) store variants (names, past cities, emails, phones) in Postgres and deduplicate; 3) automated opt-out form submission with Puppeteer including sending verification emails via SMTP and integration with a captcha-solving provider; 4) scheduled monthly rescans and a dashboard showing before/after screenshots and removal status; 5) a REST API endpoint to export CSV of removal history and a webhook for status changes. Out of scope: building proprietary patented search heuristics, SOC 2 compliance, and extensive site-coverage catalog. Include retries, error handling, logging, and automated tests for discovery, submission, and rescan flows.
How we checked3 sources · 3/3 runs agreed · evidence score 24

How the score was reached

  • Pay verdict base20
  • 3 cited sources+3
  • Price verified on pricing page+3
  • 3/3 assessment runs agreed+4
  • Hard moats found in the evidence-6
  • Evidence score24

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 · 3

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! 2 moats quoted from the page