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AI answer intelligence

AI Search Visibility you can trace to every answer.

Track a versioned prompt set across supported AI answer sources. Compare brand mentions, citations, source domains, and answer changes with every result tied to its engine, mode, locale, and capture time.

Visibility use cases

Answer the visibility questions your team already reports.

Use one prompt-level record to measure brand presence, map cited sources, compare AI answers, and follow changes over time.

Brand presence

Find the answers that mention your brand or products.

Match an approved term set against captured answers and retain the exact prompt and source context behind every result.

  • Versioned brand, product, competitor, and domain terms
  • Observed, not observed, or unavailable source state
  • Answer text and capture context ready for review
Get a brand-mention sample

Report-ready evidence

Trace every visibility metric to the answer behind it.

Each observation keeps the prompt, answer, source, mention, citation, and capture context together. Analysts can verify a dashboard result without reconstructing how it was collected.

Illustrative AI answer recordschema · versioned
prompt identity
Prompt set, prompt ID, exact text, intent group, and version.
request context
Engine, answer mode, locale, market, and supported source path.
answer
Captured answer text, modules, and explicit collection state.
brand mentions
Approved matched terms with answer or module context.
citations
Cited URLs, source domains, and available placement context.
capture context
Capture time, schema version, and prior-version linkage.

Built for your reporting model. Group and weight the underlying records by topic, market, source, brand, or competitor while keeping every metric auditable.

Comparable history

See genuine visibility change—not a changed prompt.

Version prompts and preserve the engine, mode, locale, and capture window. The resulting timeline shows whether the answer, mention state, or citation set actually changed.
Prompt timeline

Build a clean sequence of comparable answers.

Each capture uses the same fingerprint and links back to the prior version, making trends and exceptions easier to review.

  • Capture 01Baseline answer, mention set, citations, and source domains
  • Capture 02Comparable request with an explicit unchanged or changed state
  • Capture 03New version linked to the earlier answer history

Delivery options

Build the monitor yourself or receive maintained visibility data.

Choose infrastructure for full control, source-specific APIs for structured access, scheduled records for recurring analysis, or Managed Data for an operated program.

Maximum control

Run the answer collectors and reporting stack.

WebScrapingAPI supplies proxy access. Your team owns source behavior, prompt execution, extraction, normalization, history, quality, maintenance, and reporting.
VerantwortungOwner
Proxy network accessWSA
Prompt scheduling and source requestsIhr Team von Experten
Answer, mention, and citation extractionIhr Team von Experten
Quality, history, and source-change maintenanceIhr Team von Experten
Reporting, interpretation, and decisionsIhr Team von Experten

For teams with established collectors for selected AI answer sources.

Explore proxy infrastructure

From prompt to monitoring

Launch with a prompt set you can trust.

Start with representative questions, inspect real answer records, and validate the history before expanding coverage or cadence.
  1. 01 · define

    Build the prompt set.

    Group questions by topic and intent, then version the wording and match dictionaries.

  2. 02 · sample

    Capture priority AI sources.

    Review answer fields, mention matches, citations, source domains, and collection states.

  3. 03 · compare

    Validate repeat captures.

    Confirm that changed and unchanged answers remain comparable across the selected sources.

  4. 04 · launch

    Connect the delivery model.

    Use Data API, receive scheduled records, or move to an operated monitoring program.

Common questions

Plan your AI visibility program.

Understand the source coverage, record structure, history, delivery options, and inputs needed to start.

What is AI Search Visibility?

AI Search Visibility tracks how brands, products, competitors, and cited domains appear for a defined prompt set across supported AI answer sources. Each record connects the answer and its mentions or citations to the engine, mode, locale, and capture time.

Which AI answer sources can I monitor?

Dedicated Data API source pages are available for ChatGPT, Gemini, Perplexity, Grok, Microsoft Copilot, and Google AI Mode. You can select the engines and answer modes that matter to your market, with source-specific fields preserved in each record.

What is a prompt set?

A prompt set is the versioned group of questions your team wants to observe. It can be organized by topic, funnel stage, market, product, brand, or research intent so repeated captures remain comparable.

What counts as a brand mention?

Mention rules are defined from approved brand, product, domain, and competitor terms. The delivered record shows what matched in the captured answer; your team owns interpretation, taxonomy, and business conclusions.

What citation context is preserved?

When the supported answer surface exposes citations or source links, the record can retain cited URLs, source domains, citation order or placement context, the answer text, and the capture fingerprint that produced the observation.

Can I compare AI answers over time?

Yes. Re-run the same versioned prompt and request context, then compare answer text, brand-mention state, cited URLs, source domains, and collection states across capture times.

Can I build an AI visibility score from the data?

Yes. Mentions and citations are observations, not a proprietary visibility score, so your team can group and weight the underlying records around its own prompt set, markets, competitors, and reporting model.

Who maintains source collection and monitoring quality?

With scheduled datasets or Managed Data, WebScrapingAPI runs source collection, extraction, quality monitoring, history, source-change maintenance, and delivery. With Data API, WebScrapingAPI maintains the supported source extraction while your team controls prompts, scheduling, cross-source comparisons, and reporting.

What should I provide for a sample?

Send a representative prompt set, the AI sources and modes you want to compare, target markets and locales, and your brand, product, competitor, or domain terms. Add the cadence and delivery format if you need recurring monitoring.

Your prompt sample

See how your brand appears in real AI answer records.

Send representative prompts, priority AI sources, markets, and the brand or competitor terms you want to track.