SEO and marketing decision

AEO Engine

A technical user can build a narrower, self-hosted AEO pipeline (audit → generate → publish → track) but cannot cheaply reproduce the agency's human outreach, news/PR distribution, and scale of backlink placements that drive their guarantee.

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You pay

$1,597/mo

$19,164/yr

Read off the official pricing page.

You’d pay instead

$100one-off120 h to build

$400/mo6 h/mo upkeep

On cash alone, building overtakes the subscription at 1 seat.

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

  • Run an audit to find AI visibility gaps, generate answer-ready content with an LLM, publish content+schema to the client's CMS, track AI citations and visibility across LLMs, and produce weekly performance reports.

What it still won’t have

  • Human-managed outreach, negotiated placements and press distributions
  • Large-scale link-building relationships and authority placements the agency promises
  • White-glove account management and assigned strategists/agents
  • The 90-day traffic-growth guarantee and ongoing operational workforce

What remains hard

  • Brand trustTrusted by 50+ brands
  • Execution qualityYou get everything a top-tier SEO firm provides - assigned specialists, Slack-based support, strategic reviews, and accountability - plus the advanced automation, structured data management, and AI trust signals that make your business visi
Read the build prompt

First-year cost

Keep paying

Paying is—cheaper in year one.

On cash alone, building overtakes the subscription at 1 seat.

Paid seatsseats

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

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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 an MVP AEO platform using: Python (FastAPI) backend, Postgres, Redis for job queue, Next.js frontend, and OpenAI-compatible LLM API for content generation. Core features in scope: 1) site crawler and GA4/GSC ingestion endpoints; 2) a content-generation pipeline that produces answer-ready articles and JSON-LD schema; 3) CMS publishing integrations (WordPress REST API and generic headless CMS webhook) to push pages and schema; 4) scheduled AI-visibility checker that queries Perplexity/Gemini/ChatGPT endpoints or scrapes result pages and extracts citation snippets; 5) a weekly reporting endpoint and simple dashboard aggregating GA4/GSC metrics plus AI citations; 6) job retry, rate-limit handling, logging, and unit/integration tests for crawling, generation, publishing, and visibility checks. Out of scope: building a press-distribution network, managed human outreach squad, and guaranteed SLA-backed traffic uplift. Include error handling, monitoring alerts, pagination and backoff for APIs, and automated tests for the publish and visibility-check workflows.
How we checked2 sources · 3/3 runs agreed · evidence score 60

How the score was reached

  • Partly verdict base52
  • 2 cited sources+1
  • Price verified on pricing page+3
  • 3/3 assessment runs agreed+4
  • 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 · 2

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! 2 moats quoted from the page