Citable is an agentic commerce platform that helps brands win AI search by decoding how AI assistants decide which products to recommend. It builds evidence-based buyer models, scans sites for AI agent readiness, and automates content creation through AI agents that listen to customer conversations and write E-E-A-T-compliant content. The platform measures success through citation rate, mention rate, average rank, and sentiment across AI engines.
- Artificial Intelligence
- AI Agents
- Data & Analytics
- Commerce & Shopping
- Marketing Technology
- Software Only
Funding
Founders
Product
Problem
AI search engines increasingly determine which brands get discovered and purchased, yet most companies lack visibility into how these systems make decisions. Legacy brands dominate AI answers by default due to decades of training data, while newer or specialized competitors are systematically skipped regardless of product quality. Brands cannot effectively optimize for AI discovery without understanding the specific signals these engines use.
Solution
Citable provides an agentic commerce platform that interprets how AI-assisted shoppers decide, acts autonomously to win sales, and proves results in orders. The platform builds precise buyer models from real evidence—including social listening, clinical journals, sales call notes, and competitor AI search queries—rather than keyword guesses. Citable's action engine uses AI agents that monitor conversations, score topics against a question bank, draft content in the brand's voice, and iterate against E-E-A-T quality criteria before publishing. The platform also scans websites against 20+ AI crawler standards and tracks citation rate, mention rate, average rank, and sentiment across AI engines to measure impact.
Target Audience
Primary customers are brands and B2B companies that need to win AI search visibility, particularly those competing against established incumbents in categories where AI assistants default to legacy providers. The platform serves marketing teams at companies like Thyra Health, a specialty EHR provider, seeking to capture AI-driven discovery and sales.
Features
- AI agent workflow that listens to customer conversations across Reddit, YouTube, and industry journals, scores topics against a GEO question bank, and auto-drafts content with founder approval via Telegram
- Site readiness scanner that checks robots.txt, sitemap, MCP, A2A, render-ratio, and 17 additional AI crawler standards
- Four-signal measurement framework tracking Citation Rate, Mention Rate, Average Rank, and Sentiment across AI search engines
- MCP-based integration that feeds live GEO priorities, brand context, and content performance data into drafting agents
- E-E-A-T scoring loop that grades every draft against Google's quality framework and iterates until scores cross 85
- Buyer model that compounds over time, feeding every citation and competitor move back into sharper recommendations