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Customer service

AI employees that close service requests, not just answer them.

Identify the customer, read the case history, perform the approved action, update the system and hand over cleanly when the request needs a person.

Customer request
AI Customer Support Employee
Identify intent
Load customer & case context
Perform approved action
Resolve or hand off
  • Resolved
  • Human handoff
  • Phone
  • WhatsApp
  • Email
  • CRM
  • Ticketing

What AI employees take on

  • Answer repeated requests on the channel the customer used
  • Retrieve customer and case context before replying
  • Complete approved actions instead of promising a callback
  • Escalate sensitive cases with the full trail

AI employee roles for this work

  • AI Customer Support Employee

    Resolves common requests using approved knowledge, customer context and permitted actions.

  • AI Service Advisor

    Handles service-specific requests and routes policy, technical or exceptional cases to the right person.

  • AI Client Service Coordinator

    Coordinates multi-step client requests, follow-up and handoffs across teams.

Context in. Clean handoff out.

Customer context

  • Customer identity
  • Case history
  • Open request
  • Previous interactions
  • Approved service policy

The employee starts with the case context — not an isolated message.

Handoff context

  • Request summary
  • Relevant history
  • Actions already taken
  • Current case state
  • Reason for escalation

The person continues from the case — not from zero.

See the work move from request to completion

From request to resolved case

  1. Request arrives

    Phone, WhatsApp, email or another approved service channel.

  2. Identify the customer and intent

    Match the customer and understand what the request is about.

  3. Read the relevant case context

    Case history, previous interactions and permitted business context.

  4. Perform the approved action

    Only actions inside the employee's configured permissions can run.

  5. Update the system of record

    The new case state is written back to the configured business system.

  6. Confirm the outcome with the customer

    Confirm what was completed, or explain the next approved step.

  7. Escalate exceptions with full context

    Sensitive, unusual or out-of-policy cases move to a person with the case trail attached.

Works across your existing systems

  • CRMCustomer and account context
  • Ticketing systemCase history, ownership and status
  • WhatsAppCustomer messaging and confirmations
  • EmailService requests and follow-up
  • PhoneInbound and outbound conversations

What it can do — and where humans stay involved

Can do

  • Resolve requests inside its configured scope
  • Retrieve approved customer and case context
  • Perform permitted service actions
  • Update cases and send confirmations

Requires human approval

  • Goodwill gestures
  • Policy exceptions
  • Sensitive complaints
  • Unusual commercial requests

Must not do

  • Change commercial terms without authority
  • Act outside its configured permissions
  • Invent customer, order or case status
  • Commit the business to an unsupported outcome

Start small

Recommended first deployment

  1. Top recurring request types
  2. Resolution confirmation & escalation

Start with request types that have clear customer data, approved actions and defined escalation rules.

AI Workforce Assessment

Find where AI employees fit in your business

Answer a few questions and we'll identify the workflows and AI employee roles with the strongest initial fit.

Start the assessment

Results are indicative estimates based on your answers. Actual automation potential depends on workflow complexity, data quality, integrations and operating rules.

Example result
Example assessment result: 68 percent AI automation potential of assessed recurring workload.

Recommended AI employees

  • AI Customer Support Employee
  • AI Service Advisor
  • AI Client Service Coordinator

≈850 recurring staff hours/month identified for potential automation

Ready to build your first AI employee?

We'll map the first workflow, define the right AI employee, and identify the systems, knowledge and controls it needs to operate.