SEO and marketing decision

MentionDesk

A technical user can build a narrow self-hosted semantic search for one brand, but reproducing a polished commercial product with integrations, UX, and support is more work and likely why a paid product exists.

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You pay

Not priced

No pricing page we fetched carried a figure, so there is nothing to compare against. The build side is still real.

You’d pay instead

$100one-off42 h to build

$50/mo6 h/mo upkeep

No published price to break even against.

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. All MentionDesk alternatives, with the arithmetic →

What a replacement has to do

  • Crawl or ingest site content, embed and index content for semantic search, run semantic queries and ranking, present query insights and analytics in a dashboard, schedule re-crawls and incremental updates

What it still won’t have

  • Polished UI/UX and product polish
  • Commercial integrations and one-click connectors
  • Vendor support, SLAs and customer success
  • Any proprietary indexing or ranking optimizations not disclosed

What remains hard

  • Product polish and ongoing maintenance
Read the build prompt

First-year cost

No published price

MentionDesk 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
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Subscription price × seats × 12

Build it
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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 semantic brand search service using Node.js (Express) backend, Postgres+pgvector for embeddings, a crawler (simple sitemap + cheerio), and a React dashboard. In scope: site crawler, text extractor, embedding generation (OpenAI or other embedding API), vector index storage in pgvector, a semantic search API endpoint, a web UI to run queries and show ranked snippets, and a scheduler for periodic re-crawls. Out of scope: multi-tenant billing, enterprise SSO, advanced relevance tuning UI, and native mobile apps. Include error handling, logging, automated tests for crawler and search API, Dockerized deployment, and a README with setup and environment variables.
How we checked3 sources · 2/3 runs agreed · evidence score 60

How the score was reached

  • Partly verdict base52
  • An open-source build was found+5
  • 3 cited sources+3
  • Evidence score60

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.

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