SEO and marketing decision

Keysearch

A basic, useful subset (keyword search + rank tracking + AI assistant + simple audits) is realistic for a single developer to build and run; matching KeySearch's scale, data breadth, daily updates, and backlink index would require large-scale crawling and data investments and is not practical to replicate.

Visit website
You pay

$48/mo

$576/yr

Read off the official pricing page.

You’d pay instead

$50one-off30 h to build

$50/mo8 h/mo upkeep

On cash alone, building overtakes the subscription at 2 seats.

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 Keysearch alternatives, with the arithmetic →

What a replacement has to do

  • Search keywords → fetch SERP + metrics → store results and track ranks → surface keyword opportunities → generate AI-assisted content outlines.

What it still won’t have

  • Large, continuously-updated proprietary keyword database / crawl scale
  • Extensive backlink index and backlink analysis
  • Marketplace-specific data (Etsy, eBay, Amazon) and dedicated platform integrations
  • High-volume daily refreshes and historical data at scale

What remains hard

  • Product polish and ongoing maintenance
Read the build prompt

First-year cost

Keep paying

Paying is—cheaper in year one.

On cash alone, building overtakes the subscription at 2 seats.

Paid seatsseats

Money you would actually spend

Keep paying
—

Subscription price × seats × 12

Build it
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AI build —APIs + hosting —

Time you would spend

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—

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 lightweight SEO toolkit using Node.js + Express, Postgres, React, and a hosted LLM (OpenAI). Scope: (1) a keyword search endpoint that queries Google SERPs (via a SERP API or headless scraper) and stores top-10 results and positions in Postgres; (2) store and display basic metrics (volume, CPC, difficulty) from a third-party keyword-metrics API; (3) a daily rank-tracking worker (cron) that updates positions; (4) a basic site-audit crawler that reports common issues (missing title, meta, H tags, broken links) and saves issues; (5) an AI content assistant endpoint that takes a keyword + top-ranking snippets and returns an outline via OpenAI; (6) minimal React UI to run searches, view keyword results, run audits, and see AI outlines. Out of scope: building a global proprietary crawl/large backlink index, marketplace-specific keyword datasets, and white-label reporting. Include error handling, retries, logging, and unit tests for API endpoints and worker jobs.
How we checked4 sources · 3/3 runs agreed · evidence score 67

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
  • 3/3 assessment runs agreed+4
  • Evidence score67

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 →

Integrity checks

What held up, and what did not.

✓ Price read off the page✓ 3 independent runs, one answer✓ Citations limited to fetched pages! 1 moat recorded