Resolve routine customer requests and give complex cases a better handover
Connect voice and chat automation to your customer systems, knowledge and service workflows. ETT designs the interaction, the action behind it and the route to a person when judgement is needed.
What you would be buying
A voice or chat journey that resolves the routine requests you agree it should, and hands the rest to a person with the context attached.
What you receive
- Intent and journey map based on real interaction samples
- Conversation design, including what the assistant will not attempt
- Selected integrations to the systems that resolve the request
- Human handover design: when it triggers, and what the agent receives
- Testing and evaluation plan, run against held-back samples
- Service performance reporting your operations team can read
What you provide
- Representative interaction types, ideally real transcripts or recordings
- Approved knowledge sources the assistant may answer from
- Escalation policy: what must always reach a person
- Contact-center architecture and telephony details
- The languages and channels you actually need supported
How success is measured
- Successful resolution: the request was completed, not merely contained
- Repeat contact within a defined window
- Customer satisfaction on handled interactions
- Escalation quality: whether the agent received enough context to continue
- Cost per resolved interaction
Containment is one measure among these, not the definition of success. A contained call that produces a repeat contact tomorrow has resolved nothing. Supported languages, channels and integration scope are confirmed per deployment rather than promised in advance.
What can hold it up
- Telephony and contact-center change windows
- Approval of the knowledge the assistant is allowed to answer from
- Agreement on failure behavior before launch: what callers hear when a connected system is unavailable
After it goes live
Conversational systems drift as products and policies change. Plan for a review cadence and a named owner for the knowledge sources; we can run that review under a separate agreement.
Deliverables and measures describe the standard shape of this engagement. Exact scope, duration and commercial terms are agreed and confirmed in writing before work starts.
How we do the work
Conversational AI design
We define where conversational AI can create value, which interactions are suitable for automation and how the experience should work for customers and teams.
AI voice agents
We support the design and deployment of voice agents that can handle suitable customer interactions, understand intent and connect to the right systems or workflows.
Contact center automation
We reduce repetitive manual handling by connecting voice and conversational AI into contact center, CRM, ticketing and operational workflows.
Workflow-triggered conversations
We design automation so conversations can lead to action — updating a record, creating a task, routing a request or escalating an issue.
Customer conversation intelligence
We help organizations use conversation data to identify recurring issues, customer intent, process gaps and opportunities for improvement.
Multilingual and high-volume support
Where appropriate, conversational AI can support high-volume queries, multilingual interactions and repeatable processes while keeping human escalation available.
Where conversational AI can create value
Customer service and contact centers
Conversational AI can support common queries, triage requests, summarize interactions and help route customers to the right next step.
Why this matters
Customer conversations are full of operational value.
Every call, chat, query, complaint, booking request or support ticket can reveal what customers need, where processes are breaking down and which workflows are creating unnecessary friction.
The problem is that many voice and chatbot systems stop at the conversation. They may answer a question or collect information, but they do not always connect that interaction to the systems, teams and workflows that need to act on it.
ETT helps close that gap. We design conversational AI and voice automation around the full journey, from customer intent through to workflow action, data capture, escalation and performance insight.
What conversational AI means in an enterprise context
Conversational AI allows customers, employees or service users to interact with automated systems through natural language, either by voice or chat.
For enterprises, the value is not simply in having a system that can hold a conversation. The value comes when that conversation can be understood, routed, connected and acted on.
A voice agent might identify a customer's intent, check relevant information, complete a simple transaction, escalate a complex case or create a task for the right team. The strongest use cases are those where conversational AI becomes part of the workflow, not a layer sitting outside it.
Responds to prompts.
Understands intent.
Triggers workflows and creates business action.
Technology that fits the workflow
ETT works with market-leading AI, automation and voice technologies to help organizations deploy the right solution for the right use case.
The technology should fit the workflow, not the other way around. That means considering the customer journey, existing systems, data access, compliance requirements, language needs, transaction requirements and ongoing management before choosing or deploying a platform.
Where relevant, ETT can support voice AI and conversational automation using platforms such as PolyAI, alongside wider automation, data and enterprise integration tools.
These are technologies ETT implements. The relationship behind each one — formal partnership, authorised resale, or a platform we deploy — is stated on its technology ecosystem entry.
How we connect conversational AI to real customer journeys
Orient
We identify where voice or conversational AI can reduce friction, improve service journeys or create better visibility from customer interactions.
Prove
We prove the experience on a focused journey, measuring containment, resolution and customer outcomes before wider rollout.
Govern
We put consent, disclosure, recording, escalation routes and compliance controls in place so automated conversations are safe and accountable.
Scale
We implement voice agents and conversational AI into live environments, connecting them to the platforms and workflows they need across channels.
Compound
We monitor conversation performance, review escalation patterns, refine flows and analyze customer signals to keep improving over time.
Often delivered alongside
Timing, cost, access and ownership
How long does this take?
The conversation design is rarely the constraint. Telephony change windows, contact-center release cycles and knowledge approval usually set the timeline, and we sequence around them.
What drives the cost?
The number of intents in scope, how many systems sit behind them, the languages and channels genuinely required, and the depth of testing. Adding a language is not a configuration toggle — it is design, testing and ongoing maintenance.
What access do you need?
Representative interaction samples, ideally real transcripts or recordings; approved knowledge sources; your escalation policy; and details of the contact-center architecture.
Who owns the design and the data?
Ownership of the solution, its configuration and the documentation is set out in the engagement contract before work starts. Where a third-party platform forms part of the solution, that platform's own licensing terms apply to it, and we identify which components those are rather than leaving the boundary vague.
What happens when a customer gets stuck?
They reach a person, with what has already happened attached. Handover design is part of the build, not an afterthought, and we measure whether the agent actually received enough context to continue.
About this service
What is conversational AI?
Conversational AI allows people to interact with automated systems using natural language, by voice or chat. In an enterprise setting it can support customer service, internal queries, workflow routing and information retrieval.
What is a voice AI agent?
An automated system that can understand spoken requests, respond naturally and, where appropriate, connect the conversation to systems or workflows.
How can conversational AI support contact centers?
It can triage requests, answer repeatable queries, route calls, summarize interactions, support agents and trigger workflows across contact center, CRM or ticketing systems.
Can conversational AI integrate with existing systems?
Yes. It is most useful when it connects with CRM, contact center platforms, ticketing tools, order management systems, scheduling tools or knowledge bases.
Does conversational AI replace human customer service teams?
No. It should support teams by handling suitable repeatable interactions, improving routing, reducing manual effort and escalating more complex or sensitive cases to people.
Ready to connect customer conversations to action?
Request an AI session to explore where conversational AI and voice automation could improve customer journeys, reduce manual handling and create better operational intelligence.
Around four minutes. Indicative guidance based on your answers.