Challenge
QA teams had raw call datasets in CSV and XLSX format but no structured way to surface agent behavior patterns, identify coaching opportunities, or track performance over time.
AI-powered QA analytics
QA AI: Behavioral Analytics
A behavioral analytics dashboard that turns uploaded call datasets into agent-level KPIs, coaching insights, and AI-powered performance analysis — with PII redaction baked in.
ReactNode.jsPostgreSQLRechartsAI coaching
Stack
React, Vite, Node.js, PostgreSQL
AI layer
Coaching insights with PII safety
Result
50% collection rate improvement
Client context
S.P. Madrid & Associates
Category
Full stack dashboard with AI integration
AI-powered QA analytics2025–2026
QA AI: Behavioral Analytics
Call data into coaching insights.
50% collection rate improvement
Case study
The challenge, the build, and why it holds up.
Response
Built a full analytics dashboard with agent-level KPI views, drilldown filters, and AI-powered coaching workflows. Added PII redaction and context validation before any data reached external AI services.
Why it holds up
The modular architecture handles new data sources and metric types without structural changes, and the PII-safe pipeline keeps the system production-ready as AI capabilities expand.
Deliverables
- Agent-level KPI dashboard with drilldowns
- Filtered data exports and CSV/XLSX import
- AI-powered coaching insight workflows
- PII redaction pipeline before AI processing
Why it matters
Helped improve collection rate by 50% in one deployed campaign while supporting script-adherence analysis for agent coaching.
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