SEO and marketing decision

Keyword Chef

A competent developer can reproduce the core keyword discovery and bulk SERP-analysis features in about a week and run it cheaply with a SERP API; the vendor’s proprietary data/heuristics and user trust are the main things you won’t get.

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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

$50one-off30 h to build

$50/mo8 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 Keyword Chef alternatives, with the arithmetic →

What a replacement has to do

  • Search for seed terms, expand with wildcard/autocomplete, check volumes and first-page SERPs in bulk, filter by intent/volume/SERP score, save and share reports.

What it still won’t have

  • Proprietary cleaned keyword database and historical volume accuracy
  • Any undocumented backend tuning and proprietary SERP-scoring heuristics
  • Built-in user trust, reviews, and curated niche insights

What remains hard

  • Product polish and ongoing maintenance
Read the build prompt

First-year cost

No published price

Keyword Chef 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 Keyword Chef clone using Node.js (Express) backend, React frontend, Postgres for storage, and SerpAPI (or similar) for SERP data. In scope: wildcard/autocomplete expansion, bulk SERP queries, a SERP-score heuristic, filters (volume, cluster, SERP score), save/shareable report records, CSV export, and basic auth. Out of scope: paid multi-tenant billing, advanced proprietary ranking models, and large-scale scraping infrastructure. Provide error handling, retries and rate-limit handling for the SERP API, unit tests for backend endpoints, and a basic E2E test for the search->report flow.
How we checked3 sources · 2/3 runs agreed · evidence score 86

How the score was reached

  • Build verdict base78
  • An open-source build was found+5
  • 3 cited sources+3
  • Evidence score86

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