TriRank

TriRank answers a question most analytics tools ignore: when people ask AI engines for recommendations, does your brand actually show up? Instead of estimating AI traffic or scraping answer text, TriRank runs weekly probes across ChatGPT, Perplexity, Gemini and Claude and judges citations only from the structured source URLs each engine returns. That verdict is binary and verifiable: your domain is either listed as a cited source or it is not, with no guesswork layered on top of parsed prose. Underneath the AI layer, TriRank pulls real Google Search Console data every day, so clicks, impressions and average rankings come straight from your property rather than from a third-party rank tracker. Combining the two signals gives SEO and content teams a single dashboard for traditional search performance and AI citation share, making it easier to see which pages already earn AI mentions and which high-value queries still need work. For teams that want to close the gap, TriRank also drafts and publishes articles on the keywords you choose. Each draft goes through a quality gate, includes internal linking and lands as a WordPress post ready for review, turning citation gaps into a concrete publishing pipeline instead of a spreadsheet of ideas. The platform is built for marketing teams that need evidence in boardroom conversations. Every score, weight and limitation behind the methodology is published openly, so analysts can defend the numbers to stakeholders and adjust strategy based on what the engines actually return, not on a vendor's black-box model.