Indietool
AEO lite
Check if your pages are ready for AI answers
Free AEO checker that scores any URL for AI Overviews and answer engines, then shows exactly what to fix first.
•What is AEO lite?
AEO Lite is an instant answer-engine score and fix plan tool that helps users identify optimization opportunities for their content in relation to AI and answer engines. It provides a tailored fix plan based on analysis of the user's URL.
•How to use it
To use AEO Lite, simply enter the URL you want to analyze and submit your email and contact details. You will receive a detailed AEO report that includes a prioritized 90-day fix plan and custom recommendations for your site type. For deeper insights, consider requesting a comprehensive Deep Scan analysis.
•Background
AEO Lite is designed to optimize content for AI-driven answer engines, ensuring that it is effectively discovered and cited. With a focus on structured data and clear formatting, it helps users improve their visibility and authority in an increasingly AI-centric digital landscape. The app provides actionable insights and a roadmap to enhance content performance.
Frequently Asked Questions
What are the scoring buckets and what do they mean?
Your AEO score falls into one of four buckets: Excellent (85-100) indicates high optimization; Good (70-84) means solid optimization with minor improvements needed; Needs Work (50-69) shows moderate optimization with several key fixes required; Critical (0-49) signifies major issues blocking effective processing by answer engines.
How do AI Overviews and answer engines work?
AI Overviews and answer engines parse content to extract direct answers for user queries, prioritizing structured data, clear entity signals, and well-formatted question-answer pairs. They quote and cite sources directly in their responses, which is different from traditional search rankings.
How are recommendations generated?
AEO Lite analyzes your content across three pillars: Entities, Evidence, and Experience, identifying gaps in each area. It ranks recommendations by their potential impact and implementation complexity, allowing you to focus on high-impact, low-effort improvements first.
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