Which AI platforms does ABKE (AB客) GEO cover (e.g., ChatGPT, Gemini, DeepSeek)?

Coverage principle: contract-defined, source-driven

ABKE (AB客) GEO is designed for generative AI search scenarios. Exact covered platforms must follow the contract / solution checklist because different industries, languages, and compliance requirements can change the execution scope.

In common GEO deployments, the "coverage" is not limited to naming model brands. The practical execution focuses on the public web pages and knowledge bases that models retrieve, index, and cite. If those sources do not contain structured, verifiable company knowledge, the model has limited evidence to reference.

Typical AI platforms (examples, not an exhaustive list)

• ChatGPT (answer generation entry points that rely on retrieved/cited sources)
• Perplexity AI (search + citation style answers)
• Google Gemini (generative search experiences connected to web retrieval)
• DeepSeek (model entry points where retrieval and public content referencing matter)

Note: ABKE does not claim direct control over any model’s internal ranking. GEO work is implemented by improving what the models can reliably find, understand, and cite from public, indexable sources.

What ABKE GEO actually optimizes for (retrieval and citation readiness)

Most executions use public, indexable content assets as the "crawlable objects" for AI retrieval systems. Typical deliverables include:

• FAQ pages: decision-stage questions mapped to how buyers ask AI (e.g., supplier qualification, compliance, lead time, warranty).
• Technical specification pages: parameters, tolerances, materials, standards, test methods, and revision control.
• Application / case pages: use-case context, constraints, implementation steps, and measurable outcomes where applicable.

Implementation logic (precondition → process → result)

Verification and monitoring (what can be measured)

Because model outputs can vary by prompt and time, ABKE implementations commonly include monitoring of:

• Indexing / inclusion status of key pages (whether pages are discoverable via web indexing mechanisms).
• Citation / mention checks where the AI experience provides sources or allows reproducible referencing.
• Content completeness audits (whether critical supplier decision information is present: product scope, compliance evidence, delivery constraints, and transaction terms).

Scope boundaries and risk notes

• Final platform list: must follow the contract/solution checklist.
• No guaranteed "top recommendation": model outputs depend on query context, source availability, and continuous model updates.
• Dependency on evidence: if product documentation, application data, or compliance proofs are missing, the AI has limited trustworthy signals to cite.