Audit your visibility in AI search
An AI search visibility audit should distinguish what your website exposes from what an external system actually returns. Seryvon combines website signals with optional provider measurements to help investigate both questions. The open-core release is public, and the managed product is coming soon.
What the audit measures
- Technical access: crawlability, indexability and the information available on collected pages.
- Content structure: clear answers, supporting context and machine-readable information.
- Generative discovery: on-page signals and citation observations when supported providers are configured.
- Google AI search: readiness signals and provider-dependent observations.
- Agent readiness: discoverable actions, interfaces and other static indicators.
The audit pipeline assembles these inputs before applying the rules. A readiness signal is evidence about the website. A citation response is an observation from a particular provider run. Neither is a guarantee of future inclusion in an answer.
Begin with a question your audience actually asks
For example, a software team might investigate how clearly its documentation explains an integration requirement. First inspect whether the relevant page is accessible and contains a direct, supported answer. Then evaluate citation prompts that reflect that information need. This is an example workflow, not a recorded Seryvon result.
Keep the target, prompt set, provider configuration and time of measurement with the report. Review the actual responses instead of treating a single aggregate value as a complete account of visibility. The GEO guide and AEO guide explain the related content and answer-structure questions.
Separate a mention from a citation
A model can mention a brand without linking to its website. It can also answer from stored knowledge rather than retrieve the current page. The language-model connector implementation distinguishes retrieval-enabled requests from knowledge mode. This is why a mention alone should not be presented as proof that your latest content was discovered.
Supported connector code includes OpenAI, Anthropic, Gemini and Perplexity. Actual measurements depend on working credentials, available provider capabilities and request outcomes. Review a citation dry run before consuming provider quota, and preserve errors or missing measurements rather than interpreting them as confirmed absence.
Turn the audit into a bounded improvement cycle
- Review collected pages and coverage to establish what the audit observed.
- Select a concrete finding, such as unclear answer structure or missing supporting context.
- Make and review the relevant website change through your normal workflow.
- Repeat the measurement with comparable settings and examine the evidence behind any difference.
The scorecard comparison code evaluates profile compatibility. Adding providers or changing thresholds can undermine a simple before-and-after interpretation. Citation responses also vary, so a changed response does not establish that your edit caused the change.
Know what remains outside the result
An audit cannot promise rankings, AI Overview inclusion, traffic or revenue. Static ASO checks do not prove successful autonomous-agent transactions. Read the limitations and use the GSO guidance when interpreting Google-specific signals. The most useful outcome is a set of reviewable findings with a clear account of what was measured and what remains unknown.