Issue Parser
Parses support ticket to understand the issue
- •Parse ticket text
- •Extract issue type
- •Identify keywords
Understand issue, search knowledge base, provide solution, escalate if unresolved
Support ticket volumes overwhelm human agents with repetitive, easily answerable questions, creating long wait times for customers while burying agents in routine work. This agentic workflow receives support tickets, parses the issue using natural language understanding, searches knowledge bases for relevant solutions, provides step-by-step resolution guidance, confirms with the customer that the issue is resolved, and intelligently escalates to human agents only when automated resolution fails. By handling the high-volume, routine requests that consume most support capacity, this approach frees agents to focus on complex problems requiring human expertise. Organizations implementing agentic ticket auto-response achieve 50% faster response times and 30% reductions in support costs through improved efficiency, delivering 8-12x ROI. Industries with high support volumes, distributed customer bases, or technical products—such as technology, telecommunications, e-commerce, financial services, healthcare, and consumer goods—benefit most from this automation, as it dramatically improves both customer experience (through instant responses) and support team satisfaction (through elimination of repetitive work) while maintaining quality through intelligent escalation pathways.
A simple workflow that auto-responds to support tickets by searching knowledge base and providing solutions.
Issue Parser
Parses support ticket to understand the issue
KB Searcher
Searches knowledge base for relevant solutions
Response Generator
Generates response and escalates if unresolved
Receive support ticket and parse issue
Search knowledge base for relevant solutions
Provide step-by-step resolution
Confirm issue resolved with customer
Escalate to human agent if unresolved
Update knowledge base with new solutions
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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