GEO-Optimizer: The Next-Generation SEO Optimization Tool for AI Search Engines

GEO-Optimizer is an open-source project focused on Generative Engine Optimization (GEO), aiming to help websites improve their visibility in AI search engines such as ChatGPT, Perplexity, and Yandex GPT. This project provides a one-stop GEO optimization solution, adopts a modern full-stack technical architecture, designs differentiated business models for different user groups, and combines open-source and commercialization strategies—it is a practical tool to respond to the transformation of AI search.

The traditional SEO era is undergoing transformation. The rise of AI search engines has changed the way users obtain information from clicking links to directly asking questions for answers. If website content cannot be effectively understood and cited by AI, even if it ranks high in traditional SEO, it may lose its presence. GEO emerged as the times require. Unlike traditional SEO that focuses on keyword density, GEO pays more attention to enabling AI to understand, summarize, and cite content, including structured data markup, llms.txt files, FAQ optimization, etc.

Developed by SHADRINMMM, GEO-Optimizer provides one-stop GEO optimization services. The core process is: users input URL → system parses the page → generates AI-friendly optimization files (llms.txt, JSON-LD Schema markup, FAQ structured data, hosted profile pages), simplifying the complex optimization process.

Adopting a front-end and back-end separation architecture: the front-end is based on Next.js + TypeScript, supporting server-side rendering and Vercel integration; the back-end uses the FastAPI framework, relying on the Google Gemini 3.0 Flash model, deployed with Docker containerization; data storage evaluates Neon and self-hosted Postgres; file storage uses Cloudflare R2; user authentication adopts the PropelAuth solution.

Two types of target users: 1. SEO experts/agencies: agency packages cost $30-80 per month, providing multi-client management panels, unlimited websites, and API permissions; 2. Developers/freelancers: API packages (billed per website/request), WordPress plugins (free/paid versions), BYOK model (bring your own API key, with $5-10 per month infrastructure fee).

For SEO experts: promotion through Telegram professional groups (demo GIFs), case articles on vc.ru and Habr; for developers: GitHub open-source code, RapidAPI marketplace, technical articles on Dev.to/Habr, WordPress plugin directory. Adopt a free tool + paid value-added model to guide users to switch to complete packages.

GEO will change from an optional item to a mandatory one, and this project represents a new SEO paradigm. The open-source strategy (self-hosted + BYOK) meets the needs of technical users, and the hybrid model is effective. In the future, it can adapt to the evolution of AI search, such as adding support for new platforms and advanced content analysis algorithms.

All credentials must be stored in .env files and must not be submitted to Git repositories. There was an incident of R2 credential leakage; keys need to be rotated immediately, and the importance of establishing an automated key management mechanism is emphasized.