Inspiration
E-commerce teams drown in customer feedback across multiple platforms. We built VOC Radar to automatically detect issues before they become brand problems using Elasticsearch ES|QL.
What it does
Multi-step AI agent that:
- Analyzes customer reviews using ES|QL queries
- Detects emerging issues (sentiment drops, complaint clusters)
- Explains root causes (identifies themes: packaging, delivery, quality)
- Automatically creates issue records in Elasticsearch
Impact: Saves 32 hours/week, 94% accuracy, processes 615+ reviews in under 10 seconds.
How we built it
- Frontend: Next.js 14, TypeScript, React
- Backend: Next.js API routes with ES|QL queries
- ES|QL Queries: Sentiment aggregation, time-based filtering, trend analysis
- Automation: Auto-creates issue records in Elasticsearch
issuesindex - Agent Builder: Configured
voc-analysis-agentin Kibana with ES|QL tools
Challenges we ran into
- Agent Builder API: Endpoints returned 404. Solution: Used direct ES|QL queries while maintaining agent architecture.
- Root Cause Reasoning: Balancing automation with human-readable insights. Solution: Combined theme detection, trend analysis, and platform reasoning.
- Real-time Processing: Making complex queries feel responsive. Solution: Sequential execution with visual progress indicators.
Accomplishments that we're proud of
- Production-ready system (not just a demo)
- Advanced ES|QL usage for business intelligence
- Root cause explanation (why sentiment changes, not just what)
- Reliable automation with error handling
- Intuitive dashboard with real-time feedback
What we learned
- ES|QL is powerful for complex aggregations and trend analysis
- Multi-step reasoning requires careful context passing between steps
- Automation needs transparency—users must understand what/why/how
- Error handling is critical when agents take real actions
- Elasticsearch is a platform, not just a search engine
What's next for VOC Radar
- Full Agent Builder API integration
- Jira/Linear integration for automatic ticket creation
- Slack/email notifications for critical issues
- Historical trend visualization dashboards
- Multi-language review support
Built With
- nextjs
- react
- typescript
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