> ## Documentation Index
> Fetch the complete documentation index at: https://docs.wayak.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Customer service

> Draft replies, classify tickets, and uncover escalation patterns with AI agents

Customer service teams are under constant pressure to respond faster, resolve on first contact, and maintain quality across every channel. The data they need — customer history, ticket context, brand guidelines, SLA timers — lives in separate systems that are slow to navigate. Every minute an agent spends searching for information is a minute a customer spends waiting.

Wayak connects your helpdesk, CRM, and knowledge bases into a unified layer that agents can query instantly. AI agents draft replies that follow your brand voice, classify incoming tickets automatically, and surface escalation patterns your team would otherwise miss. Playbooks automate the monitoring work — SLA tracking, trend analysis, ticket routing — so your team focuses on the conversations that matter.

## Use cases

<CardGroup cols={2}>
  <Card title="Email reply drafting" icon="envelope" href="/use-cases/customer-service/email-reply-drafting">
    Read incoming emails, detect the issue type, and draft context-aware responses that follow your tone guidelines.
  </Card>

  <Card title="Ticket classification" icon="tag" href="/use-cases/customer-service/ticket-classification">
    Automatically categorize, prioritize, and tag new tickets the moment they arrive in your helpdesk.
  </Card>

  <Card title="Customer history lookup" icon="clock-rotate-left" href="/use-cases/customer-service/customer-history-lookup">
    Consolidate a customer's interactions, open tickets, and account details into a single profile in seconds.
  </Card>

  <Card title="Escalation pattern analysis" icon="chart-line" href="/use-cases/customer-service/escalation-pattern-analysis">
    Identify systemic issues driving repeated escalations and recommend process fixes backed by data.
  </Card>

  <Card title="SLA monitoring" icon="stopwatch" href="/use-cases/customer-service/sla-monitoring">
    Track response and resolution times against targets and flag at-risk tickets before they breach.
  </Card>
</CardGroup>

## Platform capabilities used

| Capability       | How it's used                                                                                                                                                                              |
| ---------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| Data sources     | Helpdesk system (tickets, interactions, SLA timers), CRM (customer accounts, contacts, contract details), email system (inbound/outbound messages)                                         |
| Knowledge spaces | Brand voice guidelines, email templates, product FAQ documents, escalation policies, refund and credit policies                                                                            |
| Semantic layer   | Objects for tickets, customers, and interactions. Metrics for first response time, resolution time, CSAT score, and escalation rate. Dimensions for category, priority, channel, and agent |
| Agents           | Support Rep for customer-facing interactions and reply drafting. Escalation Analyst for pattern identification and root-cause analysis                                                     |
| Playbooks        | Event-triggered ticket classification, scheduled SLA monitoring scans, monthly escalation trend reports                                                                                    |