Verifying access...
Real-Time Agent Assistance and Response Generation
"Your best agent resolves issues in 5 minutes because they know where everything is — your newest agent takes 15 minutes for the same ticket."
The Problem
Agents spend 30-50% of handling time searching for information across multiple systems — knowledge bases, CRM, past tickets, product docs. New agents take 3-6 months to reach full productivity because they don't know where to find answers. Response quality varies wildly between experienced and junior agents, and every interaction requires manual note-taking and wrap-up that adds 2-5 minutes of non-customer-facing time.
Current State
Agents alt-tab between 5-8 systems to find answers. Knowledge bases are outdated and poorly organized. Canned responses sound robotic and don't match context. Post-interaction summaries are inconsistent — some agents write paragraphs, others write nothing. Team leads spend hours reviewing chats to coach quality.
GenAI Solution
AI copilot monitors the live conversation and proactively surfaces relevant knowledge articles, past resolution patterns, and customer history. It generates contextually appropriate response suggestions that agents can accept, modify, or reject. After each interaction, it auto-generates a structured summary and tags the ticket. Reduces average handling time by 20-35% and cuts new agent ramp-up from months to weeks.
Key Differentiator
GenAI understands conversation context to proactively surface the RIGHT information at the RIGHT time — not just search results. Traditional knowledge search requires agents to formulate queries while handling a live customer. Copilot reduces cognitive load.
Example Workflow
- 1 Describes issue to agent
- 2 Surfaces relevant KB articles, past tickets, and customer history in agent sidebar
- 3 Generates suggested response matching conversation tone and context
- 4 Reviews, adjusts, and sends response — or searches copilot for more info
- 5 Auto-generates interaction summary and updates CRM
Prerequisites
- ticketing_system
- crm
- knowledge_base
- digital_channels
Red Flags
- No digital knowledge base
- Single-system environment
- Fewer than 5 agents
Complexity Drivers
Integration with existing ticketing and CRM systems, knowledge base quality requirements, agent adoption change management
Risk Factors
Agent resistance to AI suggestions, poor knowledge base quality degrading response quality, over-reliance on AI-generated responses
Value Metrics
average handling time, agent productivity, time to proficiency
8-12 min average handling time, 3-6 months new agent ramp-up
5-8 min average handling time, 2-4 weeks new agent ramp-up
Industry Perspectives
Specific pain points, solutions, and regulatory factors for 5 industries.
C-Suite Relevance
Key Metrics
Related Use Cases
Comprehensive Interaction Quality Analysis
You're monitoring 3% of your customer interactions and hoping the other 97% are fine.
Automated Knowledge Base Creation and Gap Identification
Your best agents solve problems brilliantly, but that knowledge lives in their heads — when they leave, it walks out the door.
Intelligent Ticket Classification and Routing
Your agents spend a third of their day sorting emails instead of solving problems — and still misroute one in three tickets.