Analytics and monitoring decision

VerifiedDR

A capable developer can reproduce the core visibility tracking and weekly plan flow in ~1 week, but the full product's marketplace, verified partner pool, Trust-adjusted scoring and guarantee are non-trivial to replicate and justify continued payment for those extras.

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Subscription$39/month ✓ verified
Initial build30 hours
Monthly upkeep8 hours + $120
Evidence2/3 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

  • Ask AI platforms the buyer questions, detect whether the target site is cited, aggregate citations and competitor sources, verify backlinks/traffic evidence, and produce a ranked weekly action list.

What it still won’t have

  • Verified marketplace of partner placements and the publisher listing pool
  • VerifiedDR's Trust-adjusted TrueDR scoring and its pre-verified backlink dataset
  • Built-in MCP/agent integrations and CLI polish
  • 12-week Visibility Score guarantee and refund handling
  • Ongoing uptime, hosting and customer support bundled by the vendor

What remains hard

  • Product polish and ongoing maintenance
Read the build prompt

First-year cost

Keep paying

Paying ischeaper in year one.

On cash alone, building overtakes the subscription at 4 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 AI-visibility tracker using Node.js (Express) + PostgreSQL + React. Core features in scope: (1) ingest a list of buyer prompts and target domain; (2) call three AI endpoints (stubbed adapters for ChatGPT, Perplexity, Google AI Mode) and store full answers; (3) extract and normalize domain citations from answers; (4) crawl and verify backlink/traffic metadata for cited pages (basic HTTP fetch + parse); (5) compute per-prompt share-of-voice, a simple impact/effort/confidence ranking algorithm, and produce a weekly action list; (6) provide a web dashboard and a small REST API/CLI to run scans. Out of scope: building a publisher marketplace, paid backlink sales, and enterprise billing. Require error handling for network failures, rate limits, retries, and include unit tests for parsing, citation-matching, and ranking logic.
How we checked4 sources · 2/3 runs agreed · evidence score 63

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
  • Evidence score63

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! 2 of 3 runs agreed; the verdict is the majority✓ Citations limited to fetched pages! 1 moat recorded