01 — Voice AI
Beyond talking. Built for outcomes.
Voice AI that handles real-world conversations, captures meaningful outcomes and gives you visibility into every interaction.
- Handles silence, interruptions and background noise
- Hands over to your team with the full context
- Full visibility across STT, LLM and TTS
Smart silence recovery
Keeps the call alive when customers go quiet.
Intelligent interruptions
Stops to listen, and ignores background noise.
Seamless human handover
Your team takes over with the full context.
Full-stack observability
See every layer: STT, LLM, TTS and infrastructure.
The challenge
Customers still call. The question is what happens next.
Phone enquiries tend to repeat: order status, appointment changes, eligibility questions, basic support. When every one of them waits for an available agent, customers wait longer and teams spend their time on questions that already have clear answers.
Routine questions compete with complex cases for the same people.
Answers vary depending on who picks up the call.
Outside working hours, enquiries simply queue up.
Useful details from calls are hard to review afterwards.
Why our Voice AI is different
AI that doesn't just talk. It understands, adapts and delivers.
Most voice bots are built for perfect conversations. Ours is built for real ones, where customers pause, interrupt, change their minds, speak over background noise and still expect to be understood.
Pillar 1
Real-world conversation intelligence
Handles silence, interruptions, noise and unclear speech, and keeps every call moving toward its goal.
Pillar 2
Deep observability
See exactly why a call succeeded or failed, across speech recognition, the language model, speech generation and infrastructure.
Conversations that feel natural
Handles silence, interruptions, noise and unclear speech the way a good agent would.
Smart silence handling
Silence doesn't mean the conversation is over.
When customers go silent, our Voice AI prompts them to continue instead of waiting indefinitely or disconnecting.
Intelligent interruption detection
Knows when to speak and when to listen.
When a customer starts speaking, the AI stops its own response and gives them the floor, for natural two-way conversations.
False interruption filtering
Background noise shouldn't break a conversation.
Unlike bots that stop at every sound, it tells genuine interruptions apart from background noise and keeps speaking when it should.
Intelligent speech recovery
Unclear speech? The conversation keeps moving.
When speech is unclear, it asks for clarification instead of guessing, freezing or abandoning the conversation.
Context-aware repetition
Asks again without making customers start over.
It repeats or rephrases only the relevant question, while keeping the rest of the conversation's context.
Natural turn-taking
No awkward overlaps. No unnecessary waiting.
Customers can pause, think and respond, without rigid, bot-like timing.
Voice AI · Appointment line
01:18
- Hi, I need to move my appointment to later this week.
- Of course. Is the booking under the number you're calling from?Understands the request
- Yes, it is.
- Thursday at 11 am or Friday at 4 pm are free. Which suits you?Uses your booking rules
- Friday, please.
- Done. You're booked for Friday at 4 pm. A confirmation is on its way.Completes the next step
Sample call · illustrative
How a call flows
From a caller's question to a clear outcome.
A proposed flow for a typical enquiry. Each step is configured and tested with your team before launch.
- 1
Customer enquiry
A customer calls with a question or request.
- 2
Understand the request
The voice bot identifies the intent and asks clarifying questions when needed.
- 3
Respond with business information
Answers draw on the knowledge and rules you have approved.
- 4
Next step or a person
The call completes a configured action, or is handed to your team with context.
Deep observability
Voice AI you can understand, measure and improve.
Don't just know that a call failed. Know why. Every layer of the pipeline is visible, so problems can be traced to their source.
End-to-end pipeline
Every layer monitored- STT trackingRecognition and transcription errors
- LLM trackingResponse times, errors and behaviour
- TTS trackingGeneration and voice delivery issues
- Faster root-cause analysis. Pinpoint whether a failure started in speech recognition, the language model, speech synthesis or the platform.
Inside one real call
Replaying a sample callBackground noise on the line00:06
Filtered out. The AI keeps speaking.
Customer interrupts mid-sentence00:14
The AI stops and listens.
Silence for a few seconds00:27
A gentle prompt to continue.
Unclear answer00:41
Rephrases only that question.
Customer asks for a person01:03
Handed over with a summary and next steps.
Outcome recorded01:10
Rescheduled · follow-up logged to CRM
Use cases
Where Voice AI can help.
Typical calls to explore together. We confirm the right fit for your operation during scoping.
Customers just talk. Voice AI handles the routine, and your team handles the rest.
Customer support
Answer common questions about orders, services or policies, and route complex cases to the right team.
“Where is my order? It was meant to arrive yesterday.”
Lead qualification
Ask a short set of qualifying questions and pass promising enquiries to sales with the details captured.
“I'm looking for a plan for a team of about fifty people.”
Appointment enquiries
Help callers ask about availability, confirm or change bookings within the rules you define.
“Can I move my appointment to Friday afternoon?”
Follow-up workflows
Support reminders, feedback requests and status updates as part of a configured journey.
“Thanks for the reminder. I'll take care of it today.”
FAQ
Questions teams often ask.
Common questions about Voice AI. If yours isn't here, we're happy to talk it through.
Workflows with recognisable questions and clear next steps are usually the best starting point: support enquiries, lead qualification, appointment questions and follow-ups. We review your call types together and recommend where voice automation makes sense and where a person should stay involved.
Your knowledge base, approved answers and process rules become the source material the voice bot draws on. We agree which sources to use, how they are structured and how your team keeps them up to date.
Voice AI supports multilingual conversations. The specific languages, accents and mixed-language patterns your customers use are discussed and confirmed during scoping, so expectations are clear before anything goes live.
You decide. Typical triggers include a caller asking for a person, a request outside the configured scope, repeated misunderstanding or a sensitive topic. The handover rules and the context passed to your team are designed as part of the project.
A clear picture of the call types in scope, the knowledge and rules the bot should follow, the actions it can take and the handover process. We then test against realistic scenarios with your team before a controlled launch.
Most voice bots can answer a call. Ours is built to handle everything that happens during it.
Smarter conversations. Clearer outcomes. Complete control. Share your call types and we'll show you how it fits your operation.