Adoption Guide
Guides feature adoption
Monitor feature adoption, flag gaps, trigger targeted guidance
Customers don't adopt key features, missing value and churning. This agentic workflow monitors feature usage, detects adoption gaps, sends in-app guidance, tracks adoption rates, and measures value realization.
Agent Architecture
Sequential agents track and guide adoption.
Adoption Guide
Guides feature adoption
Tracker
Tracks usage
Guide
Guides users
Reporter
Reports progress
Track usage
Detect gaps
Send guidance
Measure adoption
Report insights
Recommend next steps
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AI using outdated data that no longer reflects current reality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.
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
Monitor new client onboarding steps, send nudges for overdue items, and close the checklist on completion
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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