AEO Radar: Open-source Answer Engine Optimization (AEO) Monitoring Tool to Track Brand Exposure in AI Responses from ChatGPT & Others

AEO Radar is an open-source Answer Engine Optimization (AEO) monitoring tool created by developer hellowalt. It aims to help brands track their visibility and ranking performance in AI answer engines such as ChatGPT, Gemini, and Perplexity. With the rise of AI answer engines, user search behavior has shifted from browsing multiple links to obtaining a single AI-generated answer. Traditional SEO may no longer guarantee brand exposure, leading to the emergence of AEO. This tool provides data on brand mentions, rankings, sentiment trends, etc., in AI responses through automated crawling and intelligent analysis, helping brands optimize their AEO strategies.

Traditional Search Engine Optimization (SEO) focuses on a website's ranking on search result pages. However, the rise of AI answer engines like ChatGPT and Gemini has changed user search behavior: users prefer to directly obtain a single AI-generated answer. If a brand is not cited in that AI answer, it may remain 'invisible' even with excellent traditional SEO, which has driven the emergence of Answer Engine Optimization (AEO).

AEO Radar is an open-source tool whose core function is to automatically crawl AI answer engines' responses to specified keywords daily and convert them into actionable analysis dashboards. It monitors ChatGPT by default, and its architecture supports expansion to other AI engines like Gemini, Perplexity, and Claude. The modular design ensures scalability.

AEO Radar's workflow: 1. Users configure brands, keywords, and markets; 2. Claude CLI generates prompt variants for four intents: recommendation, comparison, tutorial, and purchase; 3. Playwright headless browser simulates users to obtain AI answers; 4. Claude CLI analyzes the answers and extracts data such as brand mentions, rankings, sentiment trends, competitors, and cited domains; 5. Results are stored in SQLite (switchable to PostgreSQL).

Core features include: Daily automated crawling (Playwright + stealth plugin to prevent anti-crawling); LLM-driven intelligent analysis (extracting fields like brand mentions, rankings, sentiment scores); A minimalist grayscale-themed dashboard built with Next.js + Ant Design + Recharts (including KPI cards, trend charts, competitor comparison tables, and screenshots of original results).

Usage notes: 1. Automated crawling may violate third-party platform terms of service; users must conduct their own compliance reviews; 2. Crawling accounts may be banned; it is recommended to use dedicated accounts; 3. The tool is not affiliated with AI service providers; 4. It is recommended to run at the default daily frequency to avoid triggering anti-abuse systems with a large number of queries; 5. Users are responsible for the storage and distribution of third-party content in AI answers.

AEO Radar is suitable for marketing teams, SEO professionals, and brand managers. For enterprises in regulated industries or with strict legal processes, if there are compliance risks, it is recommended to use API-based AEO tools as alternatives.

AEO Radar is an important tool innovation in the evolution from SEO to AEO. As AI answer engines change the way information is obtained, monitoring a brand's visibility in AI answers will become increasingly important. This open-source project provides teams with a low-cost, highly flexible starting point to build data-driven AEO optimization capabilities. Focusing on AEO and establishing a monitoring mechanism is a wise investment for brands to maintain their competitive advantage.