AI for customer Experience, Faster, more consistent support with less pressure on agents.
We help customer experience leaders deploy support copilots, improve self-service and use sentiment analysis. Quality holds across every channel, and the hard cases get the attention they need.
Winner, Innovative Agency of the Year UK Agency Awards 2026
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Where the work gets stuck.
Problems teams bring to us.
“Quality varies by agent and channel”
Customers get a different answer depending on who they reach and where, which erodes trust and inflates repeat contacts.
“Agents spend time searching for answers”
Information sits across systems and documents, so handling time grows and customers wait while agents hunt for the right reply.
“Self-service deflects little and frustrates customers”
Rigid help articles and basic bots fail to resolve real questions, send volume back to agents and leave customers annoyed.
“Sentiment and risk are spotted too late”
Frustrated customers and at-risk accounts get identified only after they escalate or churn, not before.
“Escalations are inconsistent and slow”
Without clear signal on what needs a human and when, complex cases bounce around or sit unresolved, and the experience suffers.
What we build for the team.
Six use cases.
Support copilots for agents
Give agents suggested responses and instant access to the right knowledge, so they reply faster and more accurately.
Response quality and consistency
Draft and check responses against approved guidance, so every customer gets a clear, on-brand answer whatever the channel.
Smarter self-service
Let customers resolve real questions in natural language, drawing on your knowledge base, and hand off cleanly when needed.
Sentiment analysis
Read tone and intent across conversations to flag frustration and risk early, so teams step in before issues escalate.
Escalation handling
Identify which cases need a human and route them with full context, so complex issues reach the right person quickly.
Consistency across channels
Apply the same knowledge and standards across chat, email and phone, so the experience holds wherever customers reach you.
How the work runs.
From mapping to measuring.
- Step 1
Understand the customer journey
We map where customers struggle and where agents lose time, then prioritise the touchpoints where AI improves the experience most.
- Step 2
Ground tools in your knowledge
We connect copilots and self-service to your approved knowledge, so answers are accurate and reflect how you actually operate.
- Step 3
Roll out with agents, not around them
We deploy AI as support for agents first, train the team and set clear escalation rules, so quality and trust improve together.
- Step 4
Measure experience and refine
We track resolution, satisfaction and handling time, then refine responses and self-service, so the experience keeps improving.
Questions about AI for customer Experience.
Will customers end up talking to a bot instead of a person?
Only where that genuinely serves them. We deploy AI first as a copilot for agents, and design self-service to resolve what it handles well, with clean handover to a person the moment a case needs one.
How do you keep responses accurate?
We ground every tool in your approved knowledge base rather than letting it answer from general knowledge, and we keep review in place for sensitive cases, so customers get answers you would stand behind.
Can this work across all our channels?
Yes. Consistency is the point, so we apply the same knowledge and standards across chat, email and phone rather than solving each channel in isolation.
Book a call about AI for customer Experience. Tell us the team and the task.
We will say where we would start.
Bring one workflow the team repeats every week.
