Publisert av Terekhin Digital Crew
AI Mention Tracking Tracks where and how often your brand appears across ChatGPT, Claude, Gemini, Perplexity, DeepSeek, and Google AI Overviews — measuring your AI Presence Rate (APR) per prompt, per model, and over time with anchor and daily measurement cycles. Unlike single-run trackers, anchor measurements run 10 queries per prompt per cycle, reducing variance by √10 and producing a statistically reliable APR signal rather than a one-off snapshot.
AI Search Ranking Insights Shows how each AI platform surfaces your brand across your monitored prompts, breaking down APR by model and visualizing performance trends over rolling measurement windows. Tracking 6 platforms simultaneously means your visibility score reflects the full AI search landscape — not a single provider that represents less than 30% of real-world AI query volume.
AI Sentiment Monitoring Classifies how AI-generated responses portray your brand — positive, neutral, or negative — at both the response level and the individual source level. This two-layer model captures sentiment shifts that response-only classifiers miss: a positive mention can cite a negatively-framed source, and single-layer tools can't tell the difference.
Competitor AI Presence Comparison Compares how often named competitors are mentioned alongside your brand in AI-generated responses, with per-competitor mention counts, mention levels, and source-level overlap analysis. Because overlap is measured at the citation source, not just the response, you know exactly which third-party pages are handing AI models the narrative — and whether they're handing it to you or your competitor.
Semantic Optimization for AI Models Provides three structured tools to improve AI discoverability: a Schema.org/JSON-LD editor, a Knowledge Graph builder that generates llms.txt and ai.txt files for AI crawlers, and a hosted MCP Server that exposes brand knowledge directly to AI models. Three independent signal channels means a brand is reachable by AI systems that ignore structured data, those that ignore knowledge graphs, and those that ignore both — coverage no single-tool approach can match.
AI-Driven Content Recommendations Generates content themes and article drafts based on your monitored prompts and top-authority sources in AI results, with multi-channel publishing to WordPress, LinkedIn, Medium, Reddit, and Bluesky. Because themes are derived from prompts that already drive AI mentions, every piece of content targets a proven AI-visible topic — not a keyword prediction that may never reach an LLM training set.
AI Visibility Reporting Delivers shareable reports combining APR trends, model-by-model rankings, sentiment scores, and competitor mentions — as a printable page, PDF, CSV, or public share link with view tracking. Combining four signal types in one report eliminates the correlation error that occurs when APR, sentiment, and competitor data are read from separate tools with different measurement windows.
AI Hallucination Detection Scans AI-generated content drafts for fabricated statistics, invented citations, and unsupported claims — flagging and replacing inaccuracies before publication, with a risk score and per-change log. The pipeline fetches the actual referenced source and runs a second LLM pass against it, catching fabrications that single-pass classifiers confirm as real because they only check plausibility, not ground truth.
Real-Time AI Mention Alerts Notifies you when your APR hits a new high or drops significantly between measurement cycles, delivered via in-app inbox and email. Alerts are triggered by a delta against the previous cycle's weighted mean — not an absolute threshold — so a drop from 80% to 74% on a high-traffic prompt triggers the same urgency as a drop from 20% to 14%, regardless of your baseline.
AI Visibility Certificates Get certificates based on verified AI Visibility results, proving that your work actually improved a brand’s presence across AI platforms.
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