Call Quality Assurance
Simulates an agentic QA workflow that automates 100% call review while ensuring human experts remain in control of high-risk or ambiguous cases.
⏱️ 3-4 mins•🎯 Starting confidence: 92%•📋 6 steps
What You'll Learn
- Understand why manual QA doesn't scale to 100% coverage
- See how work is decomposed across specialized agents
- Observe confidence-based decision gates triggering human review
- Experience Human-in-the-Loop checkpoints for quality control
- Learn how feedback loops improve future assessments
Agent Roles (5)
Orchestrator Agent
🎯coordinatorCoordinates the entire QA workflow without interrupting live operations
Responsibilities:
- • Start QA process
- • Route to agents
- • Manage human review queue
Call Ingestion Agent
⚙️processorRetrieves call transcripts and validates required data fields
Responsibilities:
- • Fetch call transcript
- • Validate metadata
- • Check required fields
Analysis Agent
🔍analyzerAnalyzes call content for topics, sentiment, and quality indicators
Responsibilities:
- • Identify call topic
- • Detect sentiment
- • Flag autofail indicators
Scoring Agent
🔍analyzerApplies QA scorecard and produces confidence-weighted assessment
Responsibilities:
- • Apply QA rubric
- • Calculate scores
- • Generate confidence level
Human QA Reviewer
👁️reviewerReviews low-confidence or high-risk calls for quality assurance
Responsibilities:
- • Review call details
- • Assess quality score
- • Provide feedback
Workflow Preview (6 steps)
🤖
Orchestrate QA Process
auto
→
🤖
Ingest Call Data
auto•+5%
→
🤖
Analyze Call Content
auto•+10%
→
🤖
Score Call Quality
auto•-20%
→
👤
Human QA Review
human•+25%
→
🤖
Finalize & Report
auto•+5%