Clovion AI
Clovion AI tracks how ChatGPT, Gemini, Claude, and Perplexity describe and recommend brands, then uses an automated content agent to write fixes for missing or weak pages. The platform measures share of recommendation per engine, benchmarks against competitors, and validates every fix through controlled experiments. An always-on analyst agent, Clove, monitors data and delivers weekly briefings with evidence.
- Artificial Intelligence
- Marketing Technology
- AI Agents
- Data & Analytics
- Software Only
Funding
Founders
Founder details are not available yet.
Product
Problem
AI recommendation engines increasingly determine which brands buyers discover, yet most companies have no visibility into how these engines perceive them. When AI mis-files or skips a brand, it rarely appears on buyer shortlists — mis-filed brands reach the right shortlists just 3% of the time — and this critical blind spot is hidden by blended metrics and one-off manual checks.
Solution
Clovion AI tracks how ChatGPT, Gemini, Claude, and Perplexity describe and recommend brands, and then fixes what it finds. The platform measures share of recommendation per engine across category searches, buyer segments, and use cases. Its content agent drafts the missing pages, weak sections, or wrong descriptions that hold a brand back, routing drafts into a human review queue. Every fix is logged as an experiment with a control group, so wins must beat the noise to prove impact. The platform also includes Clove, an always-on analyst agent that monitors all collected data, identifies patterns, and delivers weekly briefings of up to five significant findings with full evidence.
Target Audience
Marketing and brand teams at B2B companies that depend on AI-driven discovery channels and need to understand and improve how AI engines such as ChatGPT, Gemini, Claude, and Perplexity represent their brand.
Features
- Per-engine tracking across ChatGPT, Gemini, Claude, and Perplexity, never blended into a single misleading score
- Repeated sampling of prompts to establish real trends rather than reacting to single answers
- Share of recommendation metrics benchmarked against competitor brands in the same category prompt by prompt
- Automated content agent that writes fixes for each ranked recommendation, delivering drafts to a review queue before publication
- Experiment-based measurement framework with baseline and control group comparison to prove each fix's effect
- Clove analyst agent with round-the-clock monitoring, weekly briefing of up to five findings, and evidence-backed answers to user questions