AI Voice Agents & Contact Centre AI
Speech-to-speech agents that answer the phone, know who is calling, look things up in your systems and hand off cleanly to a human when they should. We have built and run this — it powers Intelina.
- Speech-to-speech
- Sub-second latency
- Live tool calls
- Human handoff
Voice is unforgiving
A chat interface tolerates a two-second pause; a phone call does not. Voice agents live or die on latency budget, interruption handling and knowing when to stop talking and transfer. We build for those constraints first, because no amount of model quality rescues an agent that feels slow or talks over the caller.
Capabilities in this practice
Each of these ships as a working system integrated with what you already run — not a slide deck or a proof of concept that stalls at the pilot.
Speech-to-Speech Agents
Real-time voice models with natural turn-taking, barge-in handling and interruption recovery — not a chained transcribe-think-speak pipeline that stacks up latency.
Caller Identification & Context
Recognise the caller on connect and pull their account, order or case history into context before the first sentence, so nobody is asked to repeat their reference number.
Knowledge Grounding
Policies, product details and procedures retrieved live from your knowledge base, so answers change the moment your documentation does.
Tool Calls Into Live Systems
Book, reschedule, check status, raise a ticket or trigger a workflow mid-conversation through authenticated webhooks against your real APIs.
Escalation & Human Handoff
Clear rules for when to transfer, with full transcript and captured context handed to the agent so the customer never starts over.
Transcripts, QA & Compliance
Recordings, transcripts, consent handling, redaction of sensitive data and searchable call history for quality review and audit.
A sequence built to de-risk, not to impress
We measure before we optimise and ship in slices, so you can stop, redirect or scale at any step with evidence rather than instinct.
- 1
Call-flow mapping
Identify the intents worth automating and, just as importantly, the ones that should always reach a person.
- 2
Latency budget
Design the end-to-end path to a target response time before choosing any component.
- 3
Knowledge & tools
Wire the retrieval layer and the authenticated actions the agent is permitted to take.
- 4
Guardrails & escalation
Define refusal behaviour, confidence thresholds and transfer triggers.
- 5
Pilot on real traffic
Run on a slice of live calls with human oversight and score every conversation.
- 6
Scale & tune
Expand intent coverage from what the transcripts show, not from what was assumed.
We run this ourselves
We build our own products on this stack. When we recommend an approach, it is one we already run in production and pay the bills for.
The things clients ask before signing
Yes. We integrate with SIP trunking and the major CPaaS providers, so numbers, routing and failover stay where they are. The agent becomes another destination in your call flow rather than a replacement for your telephony.
It transfers. Escalation triggers on explicit request, low confidence, sentiment, or any intent you have marked as human-only — and the human receives the transcript and gathered context so the caller does not repeat themselves.
Model selection is validated against recordings from your actual callers rather than clean studio audio, with confirmation prompts on high-stakes values such as amounts, dates and reference numbers.
Recording and retention are configurable, sensitive fields can be redacted in transcripts, and deployment can be scoped to a region to meet residency requirements. Consent announcements are part of the call flow where the jurisdiction requires them.
Ready to put this into production?
Tell us the problem you are trying to solve. We will tell you honestly whether AI is the right tool for it, and what it would take to ship.