Large Language Models (LLMs) are transforming how people search for and consume information. Unlike traditional search engines, LLMs generate answers directly from a mix of sources, rather than returning links to web pages. While this opens new opportunities for reaching users, it also creates a blind spot: without visibility into what these AI systems reference, brands and sites can’t fully understand their presence or performance.

LLM monitoring bridges that gap. By tracking queries, citations, brand mentions, and domain references, users gain actionable insights into emerging trends, competitive positioning, and audience behaviour in AI-driven search environments. Whether you want to benchmark performance, uncover growth opportunities, or protect your brand reputation, LLM monitoring tools provide clarity and control in a space that was previously hidden.

Pi's LLM Monitoring tools help you move from individual prompts to a broader understanding of your visibility across AI-generated search.

Explore the results generated for tracked prompts, identify the domains and URLs being cited, understand which brands are mentioned and the sentiment associated with them, and monitor how these signals change over time. Use competitor comparisons to benchmark your performance and identify where your presence is stronger or weaker.

AI Prompt Explorer provides visibility into how brands, domains, and URLs appear within AI-generated search results. By delivering question-level LLM insights at scale, it reveals which brands and URLs are mentioned, the number of domains referenced, and how these results evolve.

Use this data to benchmark performance, uncover growth opportunities, and refine strategies to align with the future of LLM-driven search.

AI Prompt Explorer aggregates queries from selected LLMs and groups, showing which domains and brands are cited most often. You can explore results by individual queries or groups, view counts of unique brand mentions, domains, and URLs, and quickly access related insights in AI Site Monitoring or AI Brand Monitoring.

AI Site Monitoring provides visibility into which sites and URLs are referenced within LLM-generated search results. By analysing citations at scale, users can benchmark site presence, track trends, and refine strategies to strengthen visibility and influence in LLM search.

This tool tracks citations for domains and URLs over time, showing total citations, query counts, and changes in visibility. Users can drill down to individual domains to view performance compared with competitors, explore the top cited directories, and identify which queries are driving references—all in one consolidated view.
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Use AI Site Monitoring to move from prompt-level results into a deeper understanding of which domains and URLs are earning citations, how that presence is changing, and how it compares with competitors.

AI Brand Monitoring provides insight into how brands are represented within LLM search results. Track brand mentions, understand sentiment (positive, neutral, negative), and identify which sources shape perception.

With these insights, users can benchmark performance, monitor sentiment trends, and refine strategies to strengthen visibility, adapt messaging, and influence audience encounters with the brand.

The tool aggregates brand mentions across queries and groups, showing totals, movement, and sentiment trends. Users can drill down to individual brands to explore mentions over time, compare performance against competitors, and identify the domains driving visibility and shaping brand perception.
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Use AI Brand Monitoring to understand the brand dimension of LLM search — from mention frequency and sentiment to the queries and cited sources associated with brand presence.

Together, Pi's LLM Monitoring tools connect prompt-level results with citation, URL, domain, brand and sentiment data. This gives you a joined-up view of your presence across AI-generated search, helping you monitor change over time, benchmark against competitors and identify areas for deeper investigation.