Approved knowledge
Define the content sources, owners and update process behind each response.
AI customer service
Automate routine service while keeping complex cases connected to the right team.
Use AI chatbots, voicebots, approved knowledge and workflow integration to resolve common enquiries, collect context and support clear escalation.
Faster routine supportConsistent approved answersClear team escalation
Service assistantLive
I was charged twice for my monthly plan.
I can help. I found two transactions and one appears to be pending. Would you like me to open a review?
Knowledge checkedWorkflow ready
Voice request understood
↗
Escalation preparedContext included for the service team
One connected service layerChat, voice, knowledge, workflows and teams
01 Understand
02 Resolve
03 Escalate
04 Improve
Where AI adds value
Use automation for repeatable work and preserve judgement for complex cases.
A practical AI service model handles repeatable requests, finds approved information and prepares the next action. Complex, sensitive or uncertain conversations move to the right team with useful context.
Interactive experience lab
See how one customer need can move across chat and voice.
Select a channel and a service scenario. The assistant changes its response, connected action and escalation path while keeping the same operating controls.
IA
Connected
Iris service assistantChat · Billing support
Suggested actionOpen billing reviewCustomer and transaction context will be attached.
Knowledge and workflow integration
Connect conversations to approved knowledge, customer data and service workflows.
Iris can help connect AI service journeys with approved content, customer records, contact-centre platforms and operational workflows. The precise integration model depends on the systems, permissions and use case.
- ✓ Approved policies, FAQs and service procedures
- ✓ CRM, account and customer-context connections
- ✓ Cases, requests, payments and service workflows
- ✓ Reporting, review and operational monitoring
AI service layerUnderstand · Respond · Act · Route
KBApproved knowledgePolicies, FAQs, procedures
CRMCustomer contextAccounts and history
WFService workflowsCases, actions and updates
CSService teamsEscalation and follow-up
Industry use cases
Apply AI customer service to high-volume, repeatable enquiries.
Each industry needs different knowledge, workflows and controls. Select an example to see where AI customer service can support a practical service journey.
Telecommunications and MVNOs
Support service, billing and plan questions across subscriber journeys.
Help customers understand plans, check service status, resolve common account questions and move complex issues to the right service queue.
Plan and account supportBilling enquiriesService-status guidance
Example service flow
CUSubscriber“Why has my data stopped?”
AIAssistantChecks plan status and explains the next step
→Connected outcomeSelf-service guidance or service-team route
Quality, control and monitoring
Set clear knowledge, boundaries, escalation and review controls.
AI service quality depends on the information it can use, the actions it is allowed to take and the situations it must escalate. Those controls should be designed before launch and reviewed in operation.
Response boundaries
Set the topics, actions and wording that the assistant can use safely.
Escalation rules
Route uncertainty, sensitive matters and exceptions to the appropriate team.
Access and review
Control data and system access, review conversations and improve knowledge, prompts and workflows over time.
Implementation note: privacy, data handling, security and regulatory requirements vary by organisation, market and use case. Final controls should be confirmed during solution design.
Implementation approach
Move from a focused use case to a service your organisation can operate.
Iris supports solution design, integration, configuration, testing, launch and ongoing improvement. Start with a clear service problem, measurable outcome and controlled scope.
Plan an AI service workshopDiscover
Choose the service problem, audience, channel and expected outcome.
Design
Define the conversation, approved knowledge, actions and escalation rules.
Connect
Integrate the required systems, data sources and contact-centre services.
Configure
Set up intents, responses, workflows, permissions and operating controls.
Test
Review service journeys, exceptions, accessibility and team readiness.
Launch and improve
Release carefully, monitor outcomes and refine the experience over time.
Start with one service problem
Which customer enquiry should be faster and easier to resolve?
Tell us about the enquiries, systems, channels and service teams involved. We will help you shape a practical AI customer-service use case.