Feedback Analyzer
Analyzes customer feedback
Analyze feedback, categorize themes, route to owners
Feedback is scattered across calls, surveys, tickets. This agentic workflow analyzes feedback, extracts themes, analyzes sentiment, routes to product/CS/sales, and tracks resolution.
Agent Architecture
Sequential agents process feedback.
Feedback Analyzer
Analyzes customer feedback
Aggregator
Aggregates feedback
Analyzer
Analyzes feedback
Router
Routes feedback
Aggregate feedback
Extract themes
Analyze sentiment
Route to owners
Track resolution
Report trends
Click any KPI to view detailed measurement guidance, formulas, and typical ranges.
Capture all agent interactions (prompts, outputs, data sources accessed) in a central, searchable system
Central inventory of all agents with metadata: owner, purpose, data sources, risk level, users
These controls help ensure secure, compliant, and auditable AI operations. High-priority controls are critical for production deployment.
AI generating false or fabricated information presented as fact
AI using outdated data that no longer reflects current reality
Inability to verify or cite the original sources of AI-generated information
Lack of proper consent for recording, storing, or processing user interactions
Risks associated with external vendors processing sensitive data
These risks should be mitigated through proper governance controls and operational procedures.
Monitor feature adoption, flag gaps, trigger targeted guidance
Handle surprise billing inquiries, explain repricing decisions, and facilitate resolution under No Surprises Act
Analyze usage patterns, flag at-risk customers, alert CSM, suggest interventions
Explore assistive AI tools that Customer Success teams use to augment these agentic workflows.
Deploying AI for customer success? Olakai monitors agent performance and ensures quality across every customer interaction.
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