How It Works: Call Quality Assurance

Workflow Overview

• •Agents execute predefined responsibilities without making decisions outside their scope.
• •Each agent has specific tasks defined in their workflow steps, ensuring predictable behavior.
• •Agents follow programmed logic to complete routine, well-defined operations quickly.
• •In this scenario, 5 of 6 steps (83%) are automated, handling repetitive tasks efficiently.

• •Human intervention is triggered when confidence drops below safety thresholds (typically 60%).
• •Critical decisions requiring judgment, ethics, or strategic thinking always require human review.
• •Edge cases that fall outside agent training data pause the workflow for human assessment.
• •This scenario has 1 designated human review point to ensure quality and safety.

• •Workflows start with an initial confidence score of 92%, representing system certainty.
• •Successful automated steps typically increase confidence (e.g., +5% for validation).
• •Complex operations or detected anomalies decrease confidence (e.g., -10% for edge cases).
• •When confidence drops below 60%, the system pauses for human review to restore certainty.
• •Human decisions can adjust confidence based on their assessment (+5% approve, +10% correct).

• •Mandatory pause points prevent runaway automation and ensure human oversight.
• •Confidence thresholds act as circuit breakers, stopping workflows that become uncertain.
• •Decision history tracking creates audit trails for compliance and learning.
• •Error handling stops workflows gracefully rather than proceeding with bad data.
• •Workflow validation ensures all steps have assigned agents and valid configurations.

Human Review Points in This Scenario

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