By default the teardown measures whether an answer engine could cite a site, judging structure alone. Deep mode adds a live visibility scan that queries ChatGPT, Gemini, Google's AI Overview, and Perplexity with buyer-style questions, then reports how often the business is actually named and which engines return zero presence. It costs a few dollars and a few minutes of API time.

How accurate is the automated score?

The generator's scores were validated against iSimplifyMe's manual AEO scanner on live sites and landed within one to two points per section. The pipeline is built to refuse to fabricate: it aborts on unreachable domains and flags cases where the crawler resolved the wrong site rather than inventing a result.

What stack does it run on?

It is a small Python pipeline: a plain-HTTP crawler with no paid keys, a single Bedrock scoring call on Claude Sonnet, and a renderer that fills iSimplifyMe's Clay report template. Finished teardowns are self-contained HTML that publish to the intel hub on S3 and CloudFront, or send directly to a prospect.

AEO Teardown Generator

Q: What does the teardown actually measure?

The generator scores seven weighted sections that sum to one hundred points: substance and depth, atomic-answer structure, schema markup, RAG-readiness, semantic clarity, internal linking, and metadata. Each section returns a score, specific findings, and a prioritized fix list, so the output reads as an actionable audit rather than a single opaque grade.

Crawls a domain, scores it on the 100-point AEO rubric via Bedrock, and renders a branded teardown.

Abstract

The AEO Teardown Generator is the engine behind iSimplifyMe's AI-visibility audits. It crawls a prospect's public pages, scores the site against iSM's canonical 100-point Answer Engine Optimization rubric in a single AWS Bedrock call, and renders a branded, self-contained HTML teardown that names the structural gap between what a site publishes and what AI answer engines can cite and recommend.

Problem

Answer engines — ChatGPT, Gemini, Google's AI Overview, Perplexity — increasingly sit between a business and its customers. Whether they cite a site depends less on traditional SEO and more on structure: atomic answers, schema, retrievable content, clean semantics.

Most businesses have no idea where they stand, and the manual audit that surfaces it is slow, judgment-heavy work that does not scale across a pipeline of prospects. The teardown turns a senior analyst's read into a repeatable pipeline.

Approach

Crawl

A plain-HTTP crawler reads the homepage and a bounded set of same-domain content pages — no paid keys, no headless browser. It extracts schema types, meta tags, heading structure, FAQ presence, and per-page text excerpts.

Score

A single Bedrock call grades the site across seven weighted sections — substance, atomic-answer structure, schema, RAG-readiness, semantic clarity, internal linking, and metadata — summing to one hundred points. Each section returns a score, concrete findings, and a prioritized fix list.

Render

The scored result fills iSimplifyMe's Clay report template — brand-locked type and color, fully self-contained, no external dependencies — and writes a single HTML file ready to host or send.

Deep mode

An optional deep pass adds a live visibility scan: it queries the major answer engines with buyer-style questions and reports how often the business is actually named, which engines return zero presence, and which competitors surface instead. This separates "an engine *could* cite you" (structure) from "an engine *does not* cite you" (live reality).

Status

Core crawl → score → render pipeline shipped.
Deep live-visibility mode shipped behind a flag.
One-command publish to the intel hub on S3 and CloudFront.
Automated scores validated against the manual AEO scanner within one to two points per section.
Built to fail closed — aborts on unreachable domains, flags wrong-site mismatches, and does not fabricate.

AEO Teardown Generator

What is the AEO Teardown Generator?