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ClosedLoop AI autonomously transforms customer conversations into product intelligence scored by business impact. No manual tagging, no predefined categories: problems surface on their own. Every recommendation traces back to real quotes and deal values.

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How it works

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Import

Data is pulled automatically from your connected sources: call transcripts, chat messages, survey responses, support tickets. Webhook-based integrations deliver data in real-time.

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AI Analysis

Each conversation is analyzed to extract:
  • Product insights: specific feature requests, bugs, pain points, improvements, discovered autonomously, not from a predefined taxonomy
  • Customer context: satisfaction, churn indicators, competitor mentions, buying behavior
  • Business context: severity, emotion, deal impact, feature area
A typical 30-minute sales call produces 5-15 product insights and 10-30 customer context records.

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Enrichment

Each insight is enriched with:
  • CRM context: linked to the customer’s company, deals, and contacts from HubSpot or Salesforce
  • Semantic indexing: enables hybrid search (keyword + meaning-based) so you find results even when exact words don’t match
  • Business outcomes: categorized by impact: retention, new sales, expansion, cost reduction

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Opportunity clustering

Related insights are automatically grouped into opportunities: product problems scored by Reach, Impact, and Confidence (RIC). This surfaces the biggest themes across all your data, including problems you didn’t know to look for.

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Zero-config, zero-maintenance

The entire pipeline runs autonomously. Connect once, and intelligence flows everywhere: your dashboard, your MCP-connected AI dev agents, your team. Insights are typically available shortly after a conversation is imported. Opportunity clusters update daily.