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.

Visit website
You pay

$3.99/mo

$48/yr

Read off the official pricing page.

You’d pay instead

$100one-off80 h to build

$150/mo20 h/mo upkeep

On cash alone, building overtakes the subscription at 40 seats.

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 is—cheaper 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