SEO and marketing decision

SEOBOT

A focused replacement that generates and publishes SEO articles (with basic internal linking) is realistic for a capable engineer to build and run; reproducing SEOBot’s full suite (backlink automation, large-scale agent orchestration, multilingual polish, and claimed dataset/traffic history) is more work and likely requires further engineering and data that a single developer won’t match quickly.

Visit website
You pay

$49/mo

$588/yr

Read off the official pricing page.

You’d pay instead

$100one-off80 h to build

$150/mo8 h/mo upkeep

On cash alone, building overtakes the subscription at 4 seats.

No open-source build does this yet

Nothing published replaces this one, so a replacement starts from an empty file. Here is what it would have to cover.

What a replacement has to do

  • Automatically research keywords and audience, generate long-form SEO-optimized articles with images and YouTube embeds, perform internal linking, and publish to a CMS via API/webhook.

What it still won’t have

  • Built-in backlink discovery & automated outreach
  • Proprietary anti-hallucination / fact-checking system as marketed
  • Pretrained large corpus of 200k+ produced articles and claimed traffic history
  • Polished multi-CMS integrations and onboarding flow
  • 50+ language support out of the box and localization coverage

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 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 an automated SEO-article generator in Node.js (Express) + PostgreSQL + a worker (BullMQ) that: 1) crawls/fetches a target site to extract pages and keywords, 2) uses an LLM (OpenAI-compatible) to generate 2–4k-word SEO-optimized articles with citations and image/embed metadata, 3) runs a simplistic fact-check step (re-query sources and surface low-confidence claims), 4) computes internal link candidates and inserts anchor links, 5) posts articles to WordPress and Webflow via their REST APIs, and 6) includes a simple UI to approve/decline drafts. Out of scope: automated backlink outreach, multi-language translation pipeline, and training custom models. Include error handling, retries, unit tests for core modules (generation, publishing, linking), and basic Docker-based deployment config.
How we checked1 sources · 3/3 runs agreed · evidence score 59

How the score was reached

  • Partly verdict base52
  • Price verified on pricing page+3
  • 3/3 assessment runs agreed+4
  • 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 · 1

Every page the run actually retrieved.

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