SEO and marketing decision

Ubersuggest

A small team can build a usable keyword-research + basic audit replacement in ~30 hours, but you lose proprietary backlink/traffic databases and brand/polish that are core to the paid product.

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SubscriptionCustom pricing
Initial build30 hours
Monthly upkeep6 hours + $50
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

  • Provide keyword suggestions and volume estimates, fetch top SERP results for a query, run a basic on-page SEO audit for a URL, store results and display rank/keyword suggestions.

What it still won’t have

  • proprietary backlink and traffic databases
  • brand trust and marketing
  • polished UX and integrated enterprise features
  • any proprietary models or score algorithms used by the vendor

What remains hard

  • Proprietary dataOur proprietary technology that helps drive innovation and efficiencies for our team.
  • Brand trustWorking With Renowned Brands
Read the build prompt

First-year cost

No published price

Ubersuggest does not publish a price we could read, so there is nothing to compare against. What building costs is below.

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 SEO toolkit using Node.js (Express) + React, Postgres, and a paid SERP API (e.g., SerpAPI or similar). Implement: (1) keyword search UI that calls a backend endpoint; (2) backend endpoint that queries a SERP API for a keyword and returns top results and basic metrics; (3) keyword suggestion generator using related searches and simple frequency scoring; (4) on-page audit endpoint that fetches a URL and analyzes title/meta, H1, status code, and Lighthouse performance snapshot; (5) persist projects/keywords/audits in Postgres and show results in the UI; (6) authentication for one user. Out of scope: building a large proprietary backlink or clickstream database, multi-tenant billing, enterprise integrations. Include error handling, logging, and unit tests for core endpoints.
How we checked2 sources · 3/3 runs agreed · evidence score 59

How the score was reached

  • Partly verdict base52
  • An open-source build was found+5
  • 2 cited sources+1
  • 3/3 assessment runs agreed+4
  • Hard moats found in the evidence-3
  • Evidence score59

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 · 2

Every page the run actually retrieved.

Integrity checks

What held up, and what did not.

✓ 3 independent runs, one answer✓ Citations limited to fetched pages! 2 moats quoted from the page