Prompt portfolio
Define the questions buyers ask when they want recommendations, alternatives, comparisons and providers.
Methodology
How serious AEO programs improve visibility in AI answers.
Answer engine optimization is not a trick. It is a repeatable evidence system for making an organization more visible, verifiable, cited and accurately represented across AI engines.
Baseline measurement
Run repeated tests across AI engines and record mentions, recommendations, citations, competitors, factual accuracy and source influence.
Entity evidence and technical access
Make the organization easier to understand and crawl through canonical facts, source mapping, structured data, stable identifiers, clear pages and bot access.
Citable content and sources
Publish assets worth citing and build legitimate presence in the external sources AI engines already trust.
Knowledge graph readiness
Resolve conflicting facts, connect products, people and relationships, and make provenance visible so graph-like systems can reconcile the entity.
Continuous iteration
Measure again, compare against competitors and prioritize the next interventions by impact.
Measure
Test real prompts and create a baseline for mentions, recommendations, citations, competitors, source influence and factual accuracy.
Intervene
Improve content, entity clarity, technical access, structured data, internal architecture and trusted external presence.
Evidence
Track which claims are backed by primary sources, which need corroboration and which contradictions make the entity harder to trust.