AI visibility tracking and community placement for brands
Discovery engine for unidentified data phenomena
Stage
Startup
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Founded
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Based in
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US
Pricing model
Freemium
Contact for pricing
Pricing
Free 7-day trial. Starter: $99/month (early bird $50/month). Growth: $299/month (early bird $150/month). Enterprise: from $499/month. All plans include AI visibility tracking and social listening. Placement credits vary by plan: Comment $10-$7, Comment with link $15-$10, Post Article $25-$15 dependi
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Key features
AI visibility tracking across ChatGPT, Perplexity, Gemini, Google AI, Claude and Grok
Daily prompt monitoring with 20-200 tracked prompts depending on plan
Social listening across Reddit, Quora, Facebook with 6-24 hour frequency
Placement Engine for publishing through established community accounts
Competitor tracking and share of voice analytics
Citation analysis showing sources AI models cite
Slack and email alerts for answer changes
Real-time thread discovery before AI locks in sources
Competitor coverage tracking across all tracked prompts
Multi-brand management and unlimited team members on Growth and Enterprise
Support for seven data shapes including time series, events, networks, and spatial measurements
32 categories spanning domains from financial markets to genomics
Discovery engine for changing relationships and recurring behaviours
Reproducible execution with documented model configuration and runtime context
Confidential compute options including Intel TDX, AWS Nitro Enclaves and AMD SEV
Developer API and GitHub integration for agent-based exploration
Support for investigating evidence and testing explanations
What makes it different
Only platform monitoring AI model recommendations, not just search rankings
Daily tracking across multiple AI models shows actual buying decision conversations
Real-time monitoring identifies emerging threads before AI locks in sources
Supports multiple engagement approaches from self-posting to managed placements
Separates phenomenon discovery from explanation, allowing rigorous investigation of root causes
Retains all outputs alongside original data for inspection and reproducibility
Works with existing data without requiring pre-identification of phenomena
Keeps execution accountable through documented model identity and configuration
BrandReply
Kavara™