Solution

AI Customer Support

Resolve routine questions instantly, give agents the context they need for complex cases, and learn from every conversation to keep improving service.

Illustration of an AI support assistant handling customer conversations

The problem

Support teams stretched between volume and quality

Customer expectations for fast, accurate answers keep rising, while support teams face growing volumes across email, chat, phone and social channels. Agents spend much of their time on repetitive questions and searching for information.

Hiring alone rarely solves the problem: training takes time, knowledge is inconsistent and peaks are hard to staff for.

Causes and impact

Why it happens and what it costs

01

Repetitive enquiries

A large share of contacts concern the same topics: order status, account access, policies.

02

Scattered knowledge

Answers are spread across articles, documents and experienced colleagues.

03

Manual triage

Tickets are read and routed by hand before anyone starts solving them.

Operational impact

  • Long waiting times during peaks
  • Inconsistent answers between agents
  • Agent fatigue from repetitive work
  • Limited insight into why customers contact you

The solution

AI that helps customers and agents

We combine three capabilities: a self-service assistant grounded in your approved knowledge, AI tools inside the agent workspace that summarise and suggest replies, and automatic classification that routes tickets to the right team with priority applied.

Conversation analytics close the loop by showing which topics drive volume and where knowledge is missing.

Main features

Key features

Self-service assistant

Answers from your help centre and policies with links to sources.

Agent assist

Ticket summaries, suggested replies and relevant articles inside the help desk.

Classification and routing

Intent, language, sentiment and priority detected automatically.

Account lookups

Secure, authenticated checks of orders, bookings or subscriptions.

Smooth escalation

Handover to people with full conversation context.

Support analytics

Topic trends, resolution rates and knowledge gaps.

High-level workflow

How it works

Illustrative example: online retailer

An online retailer’s assistant answers delivery and returns questions using live order data, while new tickets arrive in the help desk already tagged, prioritised and summarised so agents can respond more quickly.

  1. 1

    Customer asks

    Via chat, email or web form.

  2. 2

    AI understands

    Intent and details are identified; account data fetched if authenticated.

  3. 3

    Resolve or route

    Routine queries answered; others routed with priority.

  4. 4

    Agent assisted

    Agent sees summary and suggested reply, then responds.

  5. 5

    Learn

    Analytics highlight new topics and content gaps.

Integration requirements

Systems typically involved

  • Help desk and ticketing platforms
  • Knowledge base
  • CRM
  • Order, booking or billing systems
  • Identity provider

Implementation considerations

Knowledge quality

AI answers are only as good as the content behind them; plan a content review.

Clear escalation

Customers must always be able to reach a person.

Transparency

Tell customers when they are interacting with an AI assistant.

Data handling

Define what conversation data is stored and for how long.

Potential benefits

What this solution is designed to improve

Actual results depend on your starting point, data and adoption; we agree how to measure them during discovery.

Faster answers

Routine questions resolved instantly at any hour.

More consistent service

Answers come from the same approved knowledge.

Better use of agent time

People focus on complex and sensitive cases.

Actionable insight

Understand and address the root causes of contact.

FAQs

Frequently asked questions

Answers to the questions we hear most often. If yours is not covered here, our team is happy to talk it through.

Want faster, more consistent support?

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