GEO, the product, and the tech

A GEO (generative engine optimization) platform built for AI. It tracks how AI engines cite a brand, works out why they don't, produces structured content AI can extract, and keeps following the results after publishing.

SEO works on rankings in search results. GEO works on whether a brand shows up as a source in AI answers. They don't compete. Existing content becomes easier for AI to extract and cite once it is turned into Q&A pairs, JSON-LD and an llms.txt file.

Asking a model to write an article, and getting AI to cite that article, are two different problems. ReasonGo outputs Q&A pairs, JSON-LD and llms.txt in extractable formats, using only the brand's own real materials.

Doubao, Qwen, DeepSeek, ChatGPT, Perplexity, Gemini, Google AI Overviews, Microsoft Copilot, Claude and Grok. New engines get added as they launch.

A set of core business questions forms the sampling baseline. ReasonGo queries every engine with them each day, recording whether the brand is mentioned, which sources the citations come from and where competitors sit, and keeps the day-to-day changes.

Six dimensions: technical SEO, structured data, content structure, AI crawler access, page performance, and internationalization. It also visits the site the way GPTBot and ClaudeBot do, checking whether the returned HTML is complete and whether Schema and llms.txt are in place. Findings come out as implementation tickets.

Content draws only on the brand knowledge base: product parameters, certifications, transaction rules, terminology. A draft passes an AI quality check and then human review, so factual errors and compliance risks meet two gates. No invented experience, no fabricated data.

Each ticket carries the problem, the fix, the acceptance criteria and an owner. Schema, llms.txt and content can deploy automatically. Work that needs a person goes to the brand and publishes after review. The same questions are then sampled again and cited line by line.

Diagnose first, publish the assets, then keep tracking. The first round usually finishes within 30 days. How fast things move depends on how crowded the category is.

BYOK (bring your own API key) is supported, so model calls bill against each team's own key and usage stays transparent. On the platform side you pay a tooling fee only.

Customers hold their own API keys. Asset changes, reviews, publishing and corrections are logged end to end, exported on demand, and traceable. Self-hosted deployment belongs to the Enterprise tier. Every piece of content goes through human review before publishing.

Yes. Each module ships with its own translation resources, and hreflang tags plus a multilingual sitemap are generated automatically. Content goes through AI translation, then a glossary pass and human review.

It covers tiered pricing, volume quotes, sample order management and multi-currency settlement. Inquiries can be classified by intent, matched against the knowledge base, drafted as replies, and written back to the CRM.

Brand teams, teams expanding overseas, B2B companies, and marketing teams that need GEO as a system. Having your own site is not a prerequisite: start with the free diagnosis.

AI agents orchestrate multi-step tasks. Module capabilities are exposed through MCP, so other AI applications can call them. Judgments that matter, such as citation detection, content grading and ticket ordering, come from Jev as scored, structured results.

A standard protocol that lets AI applications call external tools and data safely, the same way each time. ReasonGo exposes its monitoring, audit, content and implementation modules over MCP, with type constraints and permission checks on every call.

A fast, typed decision engine for AI agents. It returns scored options in 70–500 milliseconds. Classification, routing and scoring go to Jev, so results stay stable and confidence stays calibratable.

Run the free diagnosis on your domain, or book a demo. Subscription, implementation services and enterprise engagements all work.