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Agentic customer service.

AI agents that absorb peak loads, process refunds, and answer at machine speed, so service stays steady when demand is not.

ENTERPRISE AGENTS IN CUSTOMER SERVICE

Peak loads break service teams. Agents absorb them.

Agents navigate peak demand, process customer refunds swiftly, and handle the high-volume tasks that tax human teams, for a more streamlined, responsive, proactive operation. Built in your environment, licensed to you permanently.

automation potential in customer service processes
71–81%
reduction of operating costs
30%
reduction of response times to customer inquiries
up to 80%

AUTOMATION HEATMAP

Where agents pay off in Customer Service.

  • High automation potential
  • Medium automation potential

Communication Management

  • Email Response Automation(high automation potential)
  • Chatbot Interaction Handling(high automation potential)
  • Social Media Response Management(medium automation potential)
  • Customer Inquiry Routing(high automation potential)
  • Multilingual Customer Support(medium automation potential)

Account and Order Management

  • Retrieve Customer Orders(high automation potential)
  • Customer Account Management(high automation potential)
  • Order Modification Processing(medium automation potential)
  • Shipping Status Updates(high automation potential)
  • Subscription Management(medium automation potential)

Refunds and Payments

  • Customer Refunds(high automation potential)
  • Payment Processing(high automation potential)
  • Credit Card Dispute Handling(medium automation potential)
  • Late Payment Follow-up(high automation potential)
  • Payment Receipt Automation(high automation potential)

Feedback and Complaint Handling

  • Customer Feedback Analysis(high automation potential)
  • Complaint Case Creation(high automation potential)
  • Resolution Status Updates(high automation potential)
  • Feedback-Based Alert Generation(medium automation potential)
  • Review Management(medium automation potential)

CUSTOMER SERVICE PROCESS EXAMPLES

Six examples of what agents take over.

  • Phone

    Phone intake

    The agent answers the call, holds a structured conversation, captures what the caller needs and routes it to the right person or system.

  • Payments

    Customer refunds

    Refund requests handled end-to-end: purchase details validated against transaction records, amount calculated, refund initiated in your payment system.

  • Orders

    Retrieve customer orders

    Detailed order data fetched from your order management systems — cross-referencing databases where needed — in seconds.

  • Accounts

    Customer account management

    Accounts maintained and updated automatically: modifications processed, activity tracked, data synchronized across platforms.

  • Communication

    Incoming emails automation

    Incoming emails scanned, classified by subject and content, and routed to the appropriate department.

  • Self-service

    Chatbot and FAQ handling

    Repeat questions answered on your own channels, grounded in your documentation, with a clean handover to a person when the agent cannot resolve it.

AGENT IN ACTION

How a voice intake agent works.

What it does

The agent answers the phone, holds a structured conversation in the caller's language, captures what is needed and routes it to the right person or system with the context attached.

The objective

No caller waiting in a queue for a question that takes a minute. Your team receives only the calls that need a human, already summarized.

What it does

The agent answers the phone, holds a structured conversation in the caller's language, captures what is needed and routes it to the right person or system with the context attached.

The objective

No caller waiting in a queue for a question that takes a minute. Your team receives only the calls that need a human, already summarized.

See how every agent is built →

Simulated walkthrough, five steps. One: the agent answers the call and greets the caller. Two: the caller is identified by customer reference C-10482 and matched in the CRM. Three: the agent captures the request, a delivery date change on order #58213 to 16 September, and reads it back for confirmation. Four: the agent creates case CS-2041, attaches the customer reference, order reference, requested date and call summary, and assigns it to Logistics with the status pending review. Five: the agent tells the caller the reference and that the team will confirm the date, and saves the call summary. Illustrative scenario with sample data.

Simulated — illustrative of agent behavior. Sample data.

GET IN TOUCH

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Industry Solution Catalog

Solution Catalog

A practical overview of key processes in your sector, the challenges they involve, and the AI agent solutions that address them.