Monitor how AI assistants describe your brand, which pages they cite, and how much assistant-driven traffic reaches your site.
Strong presence on comparison prompts, weak presence on pricing and alternatives.
AI visibility
See where ChatGPT and Perplexity mention competitors, skip your product, or describe your category poorly.
Citations
Track which URLs get cited, which third-party sites appear in answers, and where you need better citation coverage.
AI traffic
Separate AI-origin traffic from normal traffic so you can prove which fixes are increasing qualified discovery.
Trusted by early teams
Brands use Aparok to connect prompt visibility, citations, and AI traffic so they know which pages to fix, expand, or promote next.
Uses Aparok to monitor how ChatGPT and Perplexity surface core category prompts, pricing intent, and citation gaps across key product pages.
Uses Aparok to track how AI assistants describe the product, which competitor alternatives appear, and where answer quality breaks down.
How it works
Add a URL. See your AI visibility audit. Get a prioritized action list.
Add a URL and Aparok generates prompt watchlists that mirror how real buyers search so you can gauge visibility and sentiment.
Aparok checks how often your brand is mentioned, who else shows up, and which sites assistants trust when they form answers.
Get prioritized recommendations across technical fixes, content updates, and placements on sites that AI models already cite.
What you achieve
Aparok helps teams identify missing prompt coverage, strengthen citation-worthy pages, and measure whether AI-driven discovery is becoming real traffic.
Features
Monitor AI visibility, understand competitors, and turn signal into a prioritized optimization workflow.
FAQ
Common questions about Aparok and AI discovery.
Aparok is an AI discovery platform that combines prompt tracking, citation monitoring, AI traffic analytics, and crawl-based readiness audits.
Aparok monitors prompt watchlists across providers, records citations and brand mentions, audits site structure for LLM readability, and attributes assistant-driven traffic with a snippet.
Aparok uses a site snippet to capture assistant-attributed visits, page views, conversions, and referral patterns. That gives teams a dedicated view of AI traffic instead of mixing it into generic web analytics.
Start with clear answer-first content, stronger heading structure, visible trust signals, structured data, and pages built around the questions buyers actually ask. Aparok surfaces those gaps through audits, prompt tracking, and recommendations.
LLM optimization is the process of making your site and brand easier for AI assistants to understand, cite, and recommend. That includes content clarity, citation-worthy pages, technical structure, and monitoring how assistants respond to key prompts.
Aparok runs prompt watchlists across providers, stores answer excerpts, records brand mentions and cited domains, and shows where competitors appear instead. That makes AI visibility measurable instead of anecdotal.
Aparok is built for software teams, agencies, and operators who want to understand how brands show up in AI answers and what changes increase visibility.
No. Aparok focuses on AI discovery, prompt presence, citations, and assistant-driven traffic. It complements traditional web analytics rather than replacing them.
Each plan includes the platform, audits, reports, and AI traffic analytics. Prompt runs consume credits based on prompt count, provider count, and run frequency.