Karaya

An AI visibility platform that stores prompt runs, competitor sources, structured-data audits, and page recommendations in one workspace.

AI visibility work in one platform.

Karaya began as separate tools for prompt runs, competitor analysis, schema audits, and content review. The platform keeps their records together: model answers, cited pages, audit findings, and page-level recommendations.

Karaya visibility audit showing source citations for a model response — A stored visibility run keeps the answer and its citations together.

Karaya model answers view showing an AI response and its sources — The underlying model answer stays available for review.

Visibility runs

Karaya runs selected prompts across AI assistants and stores each answer with the model, citations, and run context. The records show where a brand appears, the language used to describe it, and the prompts that produce citations.

Competitive analysis

Each visibility run identifies competitor mentions and cited pages. Reviewing those pages shows the definitions, examples, supporting facts, internal links, and source material associated with the answer. That gives the content work a direct reference point.

Structured data and site structure

The structured-data audit reviews JSON-LD alongside entity details, headings, internal links, definitions, and supporting pages. Audit findings stay connected to the prompt runs and cited competitor pages that prompted the review.

Runs, audits, and recommendations

Karaya combines the original tools: mini visibility runs, competitor analysis, schema audits, and content review. It keeps the underlying answers, cited sources, audit results, and page recommendations together. The same prompts can be rerun after page changes.

Review your AI visibility.

Start with the prompts, competitor pages, citations, and site structure connected to your brand.

Talk about AI visibility