What containment rate is realistic for voice AI?

For well-scoped, high-volume transactional intents, 35–60% containment is a defensible target in year one; broad, unscoped deployments typically underperform that range.

Can voice AI run on an existing IVR?

Yes — conversational front-ends commonly sit in front of a legacy IVR and route to existing flows, which avoids a full IVR rewrite during the pilot.

What drives voice AI cost?

Streaming speech-to-text and text-to-speech minutes, LLM tokens per turn, telephony minutes and integration effort — usually quoted per contained call rather than per seat.

What do voice AI implementation services include?

Call-data analysis, intent design, conversation and escalation flows, platform and model configuration, telephony and CRM integration, testing, phased cutover and managed operations.

How much does voice AI cost?

Cost is driven by minutes: speech and inference per minute, telephony and platform charges, plus build and run. We forecast per-intent cost against expected containment before committing to scope.

How do you migrate from IVR to conversational AI?

We map every IVR path to an intent, rebuild flows with natural intent capture, keep DTMF fallbacks where needed, and cut over queue by queue with containment and abandonment monitoring.

Will callers still reach a human?

Yes. Escalation is designed first — the voice agent passes intent, entities and transcript to the live agent so customers never repeat themselves.

How long does a voice AI implementation take?

A first production intent set typically ships in 8–12 weeks, with additional intents added in two-to-four week increments.

Voice AI

Voice AI implementation services for the enterprise contact center.

Pronix delivers voice AI implementation services and voice AI consulting for enterprise contact centers. We design and build low-latency voice agents that authenticate callers, capture intent and complete transactions with warm handoff — including IVR to conversational AI migration on NICE CXone, Genesys Cloud CX, Amazon Connect, Five9 and Google CCAI — with a voice AI cost model agreed before build starts.

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Enterprise voice AI and IVR modernization for cloud contact centers — pronix.ai.

How we deliver

Assess → Design → Pilot → Implement → Scale → Operate.

One delivery model that moves from strategy to production without handoffs — with managed operations built in.

See how we deliver

Implementation · Voice AIphased delivery

Assess

Top-intent analysis and containment sizing.

wk 1

Design

Conversation, auth and handoff design.

wk 3

Pilot

One intent, measurable containment KPI.

wk 5

Implement

CCaaS integration and system-of-record wiring.

wk 7

Scale

Additional intents, languages and geos.

wk 9

Operate

Managed voice ops with continuous tuning.

wk 11

50–75%

Containment on top intents

< 800ms

Turn latency

-30%

Cost per contact

+10pt

CSAT on self-service

The enterprise challenge

Legacy IVR trained customers to press zero.

Menu-tree IVR is a tax on the customer and the business. Voice AI, done right, is faster than a menu and often faster than a live agent for the top intents.

Latency is UX
Anything over 800ms feels robotic. Enterprise-grade voice requires an end-to-end latency budget.
Authentication in-line
If auth breaks the conversation, the customer bails. Voice AI must authenticate mid-flow.
Warm handoff or bust
A cold transfer to a live agent burns the goodwill the agent just earned.

Capabilities

Voice AI engineered to enterprise standards.

Low-latency stack

ASR + LLM + TTS with a budget tuned for sub-second turn-taking.

Authentication in-flow

Knowledge-based, voice-print or CRM-driven auth without breaking the conversation.

Transactional workflows

Payments, scheduling, account changes and status lookups — end-to-end, not just intent capture.

Warm handoff

Live agent receives call, transcript, intent, sentiment and context in the CCaaS desktop.

Multilingual

Native handling of major global languages with dialect and accent tuning.

CCaaS-native

Deployed on Amazon Connect, Genesys, NICE, Five9, Salesforce Agentforce, Google CCAI and Dynamics 365 CCaaS.

How we deliver

A six-step model, from assessment to managed operations.

Every engagement follows the same rhythm — so business, IT and delivery stay aligned from opportunity to outcome.

Assess

Top-intent analysis and containment sizing.

Design

Conversation, auth and handoff design.

Pilot

One intent, measurable containment KPI.

Implement

CCaaS integration and system-of-record wiring.

Scale

Additional intents, languages and geos.

Operate

Managed voice ops with continuous tuning.

Where it lands

Use cases already in production with enterprise clients.

Payments and billing self-service

Authenticated bill lookup, payment and payment-arrangement flows end-to-end on voice.

Appointment scheduling

Book, reschedule and cancel appointments with real-time slot availability from source systems.

Claims first-notice-of-loss

Structured intake with sentiment-aware routing to the right adjuster team.

Care navigation

Symptom triage and provider routing for healthcare, with escalation to nurse lines when needed.

Runs on

Partner platforms we implement

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Runs on

Grounded on your data. Governed on day one.

Every platform we implement is only as good as the retrieval, connectors and controls behind it. These are the horizontal solutions we ship with every engagement.

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Quick answer

What is required to implement voice AI in an enterprise contact center?

Enterprise voice AI implementation needs four things: a ranked intent set from real call transcripts, a telephony path into the CCaaS platform, hand-off rules that pass full context to a human agent, and an evaluation harness that scores containment and escalation quality on production traffic. Most programs reach live containment on top intents in 8–12 weeks.

Last reviewed 2026-08-05

Intents come from transcripts, not workshops

We mine existing call recordings and IVR paths to rank intents by volume and automation feasibility, so the pilot targets calls that actually dominate the queue.

Telephony and CCaaS integration is the hard part

Latency budgets, barge-in behaviour, SIP or platform-native media routing and CRM screen-pop on transfer determine whether a voice agent feels usable. These are scoped before model selection.

Escalation quality is a first-class metric

Containment without clean escalation destroys CSAT. Every hand-off carries the transcript, captured entities and the reason for transfer into the agent desktop.

Voice AI consulting

Voice AI consulting starts with your call data. We mine transcripts and IVR paths to size containable volume, then score intents by feasibility and value, choose the speech and model stack, and design the authentication, disambiguation and escalation flows before anyone writes a prompt.

Transcript and IVR path mining
Intent feasibility and containment sizing
Speech, model and platform selection

IVR to conversational AI migration

IVR to conversational AI migration replaces menu trees with natural intent capture without stranding callers. We map every existing IVR path to an intent, keep DTMF fallbacks where regulation or accessibility requires them, and cut over by queue with real-time containment and abandonment monitoring.

Full IVR path to intent mapping
DTMF fallback and accessibility retained
Queue-by-queue cutover with live monitoring

Voice AI cost

Voice AI cost is driven by minutes, model and telephony, not licences alone. We forecast per-minute inference, speech and platform charges against expected containment so the business case is net of run cost — and we tune latency and model selection during operations to hold it.

Per-minute cost forecast by intent
Containment-adjusted business case
Ongoing latency and model cost tuning

Voice AI implementation and operations

Voice AI implementation continues after launch: barge-in and latency tuning, ASR vocabulary and accent handling, prompt and disambiguation updates, containment reviews and regression testing on every release, run by a named pod against agreed SLAs.

Latency, barge-in and ASR tuning
Regression suites on every release
Monthly containment and CSAT reviews

Talk to us

Scope your voice AI implementation

We map your top intents, telephony path and hand-off rules, then size the pilot that proves containment on real traffic.

Intent and containment sizing
Telephony and CCaaS integration path
Pilot scope with acceptance criteria

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Explore next

Related capabilities and guides

Frequently asked

Questions buyers ask us first.

What do voice AI implementation services include?: Call-data analysis, intent design, conversation and escalation flows, platform and model configuration, telephony and CRM integration, testing, phased cutover and managed operations.
How much does voice AI cost?: Cost is driven by minutes: speech and inference per minute, telephony and platform charges, plus build and run. We forecast per-intent cost against expected containment before committing to scope.
How do you migrate from IVR to conversational AI?: We map every IVR path to an intent, rebuild flows with natural intent capture, keep DTMF fallbacks where needed, and cut over queue by queue with containment and abandonment monitoring.
Will callers still reach a human?: Yes. Escalation is designed first — the voice agent passes intent, entities and transcript to the live agent so customers never repeat themselves.
How long does a voice AI implementation take?: A first production intent set typically ships in 8–12 weeks, with additional intents added in two-to-four week increments.

Next step

Book a working session with our voice ai team.

30 minutes. Your architecture, your data, your KPIs. You leave with a concrete pilot outline and a business case worth defending.

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