AI that understands how your customers actually speak
A cloud contact centre with autonomous voice agents, live agent assist and automated quality scoring on every call — with recognition tuned to the accents and languages your floor actually handles, wherever it sits. Running on a softswitch we built ourselves, so it bends to your workflow rather than the other way round.
Zephyr AI Call Centre at a glance
- Three layers of AI — autonomous voice agents, live agent assist, and automated QA across every interaction
- Tuned per deployment — accuracy measured per accent group, not one global average
- Inbound and outbound — skills-based queues plus a predictive dialler with pacing and DNC enforcement
- Runs on our own switch — routing, scoring rubrics and reports built to your spec
- POPIA-ready recording — consent capture, retention policy, legal hold and access auditing
- Billed in your currency — USD, ZAR, EUR or GBP — with follow-the-sun support
"AI call centre" means three different things. You need all three.
Most vendors sell one layer and call it a platform. A voice bot with no quality feedback loop degrades quietly. QA analytics with no live assist tells you what went wrong after the customer has already gone.
1 · Customer-facing
Autonomous voice agents. Handle balance enquiries, order status, appointment confirmation, delivery tracking and after-hours overflow from greeting to resolution. They hand off to a person the moment the conversation leaves their scope, carrying the full context with them.
2 · Agent-facing
Live assist during the call. Surfaces the account history, the next best action, objection handling and compliance prompts while the agent is still talking. New starters reach competence faster because the guidance is in front of them, not in a manual.
3 · Leader-facing
Automated QA on 100% of calls. Every interaction transcribed, scored against your rubric, sentiment tracked and coaching flags raised. You stop sampling 2% of calls and hoping it's representative.
Most AI voice was not trained on your customers
Speech recognition accuracy varies sharply by accent, and the industry knows it — bias across accents and dialects is a standing risk flagged in every serious evaluation of AI voice. The platforms leading those evaluations are trained predominantly on North American English, which is not who most of the world's contact centres talk to.
A model that scores well in Ohio will mishear a Lagos accent, a Glaswegian one, or a caller code-switching between two languages mid-sentence — and every mishearing is a misroute, a wrong answer, or a customer asking for a human. We know this ground well: our home market runs eleven official languages and constant code-switching, which is about the hardest test there is.
- Tuned against your own call audio, not a US-English baseline
- Accuracy reported per accent group so you can see where it is weak before you deploy
- Code-switching handled rather than treated as recognition failure
- Multilingual deployments where your floor handles more than one language
- Escalation on low confidence — the agent hands off rather than guessing
The full contact centre, not an AI add-on
The AI sits on top of a complete contact centre. If you switched every AI feature off tomorrow you would still have a capable operation running.
| Area | Capability |
|---|---|
| Inbound routing | Skills-based routing, priority queues, overflow, time-of-day plans, IVR with nested menus and callback in queue |
| Outbound | Predictive, progressive and preview dialling, pacing control, answering-machine detection, DNC list enforcement, per-CLI reputation tracking |
| Agent tools | Browser softphone, warm and cold transfer, conference, hold with custom music, dispositions, wrap-up timers, internal chat and presence |
| Supervisor | Live wallboards, whisper, barge-in, silent monitor, queue reassignment, agent state override |
| AI voice agents | Autonomous inbound handling, intent detection, confidence-based escalation, context handoff to a live agent |
| Agent assist | Real-time transcript, next-best-action prompts, knowledge surfacing, compliance reminders |
| Quality | Transcription of every call, automated scoring against your rubric, sentiment tracking, coaching flags, searchable transcript archive |
| Recording | Selective or full recording, retention policy per tenant, legal hold, tamper detection, consent capture, access audit log |
| Reporting | Live and historical queue metrics, agent performance, ASR and MOS per call, scheduled report delivery, CDR export |
| Integration | REST API, webhooks, CRM screen-pop, click-to-dial, custom integrations built to spec |
Where AI works, and where it doesn't
Plenty of AI contact centre projects fail to deliver return because the wrong calls were automated. We would rather scope this correctly than sell you containment you won't reach.
Good candidates for automation
- ✓Balance and account status enquiries
- ✓Order tracking and delivery status
- ✓Appointment booking, confirmation and rescheduling
- ✓Lead qualification before routing to a closer
- ✓After-hours and peak overflow capture
Keep these with a person
- !Complaints and anything emotionally loaded
- !Retention and cancellation conversations
- !Debt collection and financial hardship
- !Exception handling outside documented policy
- !Anything where a wrong answer creates liability
Guardrails matter as much as capability. An AI agent that invents a refund policy or promises something you can't honour costs more than the call it saved. Ours are scoped to defined intents, escalate on low confidence, and never improvise policy.
AI call centre questions
What is an AI call centre?
An AI call centre uses speech recognition and language models to handle parts of a customer conversation that previously needed a person. In practice this covers three layers: autonomous voice agents that resolve routine calls end to end, real-time assistance that guides a live agent during a call, and automated quality assurance that scores every interaction instead of a small manual sample.
Will the AI understand my customers' accents?
Most platforms are trained predominantly on North American English and degrade on everything else — African, South Asian, Filipino, regional British and code-switched speech. We tune recognition against your own call audio during onboarding and measure accuracy per accent group rather than reporting a single global figure you cannot verify.
How much of my call volume can AI actually handle?
Containment depends entirely on your call mix. Repetitive transactional calls are strong candidates. Complex, emotional or exception-heavy calls should route to a person. We measure containment on your real traffic during a pilot before you commit to anything.
Does the AI replace my agents?
It removes repetitive volume so agents spend time on calls that need judgement. Most operations redeploy capacity into retention, upsell and complex support rather than cutting headcount. Agent-facing AI also shortens ramp time for new starters.
Is call recording with AI analysis POPIA compliant?
It can be, provided you have a lawful basis, capture consent where required, tell the data subject what is recorded and why, apply retention limits and can honour deletion requests. We provide consent capture, retention policies, legal hold, access auditing and subject access request tooling to support that. Your own processing purposes still need to be documented on your side.
Can the contact centre be customised for our workflows?
Yes. Because we wrote the underlying softswitch, routing logic, scoring rubrics, dispositions, wallboards and integrations can be built to your specification rather than selected from a fixed feature list.
Can we run this as a white-label product for our own clients?
Yes. BPOs and resellers run the contact centre under their own brand with their own tenant hierarchy and markup. See white-label licensing.
Pilot it on your own traffic first
We'll run the AI against a sample of your real calls and report containment and recognition accuracy before you sign anything.