Rank offers an automated monitoring platform that continuously queries major large‑language‑model APIs (e.g., ChatGPT, Claude, Gemini, Grok, Perplexity) with real‑world prompts to track brand mentions across languages and markets. The service aggregates occurrence data into a “Rank Score,” applies NLP analysis to identify the keywords and content signals influencing model recall, and provides data‑driven recommendations and competitive benchmarking to improve AI‑driven visibility.
Funding
Funding not disclosed
Founders
Product
Problem
Brands increasingly rely on generative AI assistants (e.g., ChatGPT, Claude, Gemini, Grok, Perplexity) for consumer discovery, yet there is no systematic way to know whether a brand appears in model responses or why it is omitted. This lack of visibility makes it difficult to manage narrative control, benchmark against competitors, and optimize content for AI-driven search.
Solution
Rank provides an automated monitoring platform that continuously scans major large‑language‑model (LLM) APIs using real‑world user prompts to detect brand mentions. The service aggregates raw occurrence data, normalizes it across languages and markets, and surfaces a “Rank Score” that quantifies visibility per model. A reasoning layer analyzes the lexical and contextual signals (keywords, product features, document provenance) that drive inclusion or exclusion, while an action engine translates those insights into concrete recommendations—such as content localization, schema updates, or prompt tuning—to improve future AI recall. Users can also benchmark their visibility against defined competitors, track changes over time, and receive automated alerts when significant shifts occur.
Target Audience
The primary customers are brand and marketing teams at SaaS, technology, consumer product, and media agencies that need to ensure their narrative is captured by AI assistants, as well as SEO/AI specialists who manage cross‑channel digital presence.
Features
- Visibility Tracker that queries ChatGPT, Claude, Gemini, Grok, and Perplexity with configurable prompts, personas, and market segments
- Multi‑language support (English, Dutch, German, French, etc.) to surface regional visibility gaps
- Reasoning Layer that applies NLP parsing and feature attribution to identify the exact keywords, product attributes, and document signals influencing model recall
- Action Engine delivering prioritized, data‑driven recommendations (e.g., content enrichment, schema markup, localized assets) to boost AI inclusion
- Competitive Benchmarking dashboard that compares Rank Scores, bias metrics, and mention frequency against selected rivals across each LLM
- Configurable monitoring parameters (prompt libraries, target industries, buyer personas, geographic regions) with a single‑click setup
- Daily automated reporting and real‑time email alerts for notable visibility changes
- Role‑based web portal with exportable CSV/JSON data feeds for integration into existing analytics or BI tools