Problems we address
- Brand and service facts conflict
- Important facts exist only in images or inaccessible UI
- Sources, authorship and project evidence are missing
- AI referrals and observed questions are not recorded
We improve machine-readable identity, answer quality, evidence and observation instead of reducing AI visibility to llms.txt or ranking promises.
Who it is for
Companies that want their services to be understood and cited accurately in AI-assisted research journeys.
Target business outcome
Consistent entity and service information, accessible answers, source-backed evidence and measurable referral context.
Scope options
Use cases
Publishes who it serves, scope, evidence and limits in direct language.
Connects common questions to sourced guides, services and real projects.
Maintains one identity while writing natural answers in each language.
Working approach
They share crawlability, architecture and content quality; GEO adds explicit answers, sources, entity consistency and observation.
No. It may be a supporting directory, not a ranking guarantee.
No. OpenAI documents search discovery and training controls separately.
Crawler access, indexation, response consistency, referrals and dated question checks are recorded.
Project enquiry
A short brief is enough. We clarify the suitable solution, integrations and next step during the discussion.