Which messaging channels does Pronix support?

Web chat, mobile in-app messaging, WhatsApp and RCS, unified under one intent and context model with the existing CCaaS platform.

Can these virtual agents complete transactions, not just answer questions?

Yes — they are integrated with backend systems to complete transactional intents where the use case calls for it, not limited to FAQ responses.

What happens when a conversation needs a human agent?

The full transcript and captured context are handed to the CCaaS platform and agent desktop so the escalation preserves everything the customer already provided.

What does conversational AI consulting include?

Bot and channel audit, intent taxonomy, dialog and knowledge design, platform selection, integration architecture, build, evaluation and post-launch tuning.

How long does conversational AI implementation take?

A first channel with a focused intent set typically goes live in 6–10 weeks; additional channels reuse the same intent model and ship considerably faster.

What makes conversational AI integration difficult?

Identity, entitlement-aware knowledge and live-agent handoff. Without authenticated CRM context, assistants can answer questions but cannot resolve them.

Do you offer AI chatbot consulting for bots we already built?

Yes. We audit containment, abandonment and knowledge coverage, then recommend which flows to retire, rebuild or extend before adding anything new.

Which conversational AI platforms do you work with?

Kore.ai, Google Dialogflow CX and CCAI, Microsoft Copilot Studio, IBM watsonx Assistant, Amazon Lex and the native assistants in Genesys, NICE and Five9.

How is a conversational AI engagement priced and what drives cost?

We price a fixed-fee assessment and design phase, a milestone-based build against agreed intents and channels, and a monthly managed-run fee once live, plus optional staff augmentation billed per person per month. Cost is driven by the number of channels, intents and systems-of-record integrations rather than the AI models themselves.

How long does it take to reach a first production release?

A first channel with a focused intent set typically reaches production in 6 to 10 weeks, with additional channels shipping faster because they reuse the same intent model, knowledge layer and CRM integration.

Which CCaaS platforms does conversational AI integrate with and how do we choose?

We integrate conversational AI with Amazon Connect, Genesys Cloud CX, NICE CXone, Five9, Google CCAI and Kore.ai for live-agent handoff. Platform choice follows your existing CCaaS and CRM investment and how much native bot capability that platform already provides.

What does managed support for conversational AI include?

Managed support covers intent and knowledge tuning, containment and abandonment monitoring, regression and safety evaluation on every release, and incident response under a documented SLA, with business-hours coverage as standard and 24x7 coverage available.

What does certified conversational AI talent cost, notice period and delivery locations?

Certified conversational AI engineers and dialog designers are billed at a monthly per-person rate with a standard notice period for ramp-down. Delivery is led from our Plainsboro, NJ headquarters, staffed from our Hyderabad global delivery center, plus London and Dubai for regional coverage.

Conversational AI for Contact Centers

Book a strategy session Explore the reference architecture

60–80% — Digital containment

Outcomes

Measurable outcomes, not slideware.

Conversational AI engagements are designed around a small set of business outcomes we commit to at kickoff.

Book a scoping call

ROI modellive calculator

Inputs

Digital containment60–80%

Unified stack across channels1x

Cost per digital contact-40%

Output

Digital CSAT+20pt

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 · Conversational AIphased delivery

Assess

Channel and intent analysis.

wk 1

Design

Conversation, knowledge and workflow design.

wk 3

Pilot

One channel, one intent family.

wk 5

Implement

Integration and CCaaS handoff.

wk 7

Scale

Additional channels, languages and geos.

wk 9

Operate

Continuous knowledge and intent tuning.

wk 11

60–80%

Digital containment

Unified stack across channels

-40%

Cost per digital contact

+20pt

Digital CSAT

The enterprise challenge

Digital bots without context are a modern IVR.

Most conversational AI programs stall because bots don't carry customer state across channels, don't know the product deeply, and can't complete transactions.

Channel silos
Web bot, WhatsApp bot and app bot each built by a different team on a different stack.
No transactional depth
Bots that answer FAQs but can't change an order or update an appointment don't move the needle.
No CCaaS handoff
When the bot fails, the customer starts over with a live agent instead of continuing the conversation.

Capabilities

One conversational layer across every digital channel.

Unified intent & context

One intent model, one context store, one knowledge layer across all digital channels.

Transactional workflows

Order changes, account updates, appointment management and payments — end-to-end in the conversation.

Governed knowledge

RAG grounded in current product, policy and playbook content with citation and access control.

CCaaS handoff

Warm handoff to a live agent with transcript, intent and customer context intact.

Rich channel support

Web, mobile, WhatsApp, RCS, Apple Messages, Facebook Messenger, Instagram and voice.

CRM integration

Native integration with Salesforce, Dynamics 365, Zendesk, ServiceNow and custom systems of record.

Reference architecture

The conversational AI reference architecture.

One conversational layer across voice and digital, wired into your CCaaS platform and CRM rather than bolted alongside them.

Customer channelsSystems of record

01
Customer channels
Voice, web chat, mobile app, WhatsApp, SMS and social — one conversation model, channel-specific presentation.
02
NLU & dialog orchestration
Intent, entity and LLM-based understanding, disambiguation, context carry-over and deterministic dialog policy for regulated flows.
03
Knowledge & fulfilment
Grounded retrieval over approved content plus transactional fulfilment through APIs — order status, payments, appointments, account changes.
04
Escalation & agent handoff
Warm transfer with full transcript, intent and authentication state so the customer never repeats themselves.
05
CCaaS & systems of record
Amazon Connect, Genesys Cloud, NICE CXone or Five9 alongside CRM, order management and billing.

Definition

What is conversational AI?

Conversational AI is technology that lets a customer interact with an enterprise in natural language across voice, chat, messaging and email — understanding intent, holding context across turns, retrieving and updating data in business systems, and handing over to a human with that context when needed. In a contact center it is measured on containment, resolution accuracy, escalation quality and customer satisfaction.

Designing a conversational AI program in five steps

Step 1
Rank intents by value
Use transcript and ticket mining to rank intents by volume, handle cost and automation feasibility.
Step 2
Choose the channel order
Automate the channel where the intent actually arrives — chat-first for status, voice-first for urgency.
Step 3
Ground answers
Connect approved knowledge and systems of record so responses are cited and account-accurate, not generic.
Step 4
Define escalation
Set the confidence and sentiment thresholds that trigger a warm handover with full transcript context.
Step 5
Operate and expand
Review containment and CSAT by intent, retire failing flows, and add the next intent tier each quarter.

Conversational AI vs rules-based chatbot

Conversational AI vs rules-based chatbot
Dimension	Conversational AI	Rules-based chatbot
Understanding	Intent and context from natural language	Keyword and decision-tree matching
Context across turns	Retained	Usually reset per node
Transactional depth	Reads and writes systems of record	Links out or opens a ticket
Maintenance	Knowledge and prompt updates	Flow rebuilds per change
Failure mode	Escalates with context	Dead ends and loops

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

Channel and intent analysis.

Design

Conversation, knowledge and workflow design.

Pilot

One channel, one intent family.

Implement

Integration and CCaaS handoff.

Scale

Additional channels, languages and geos.

Operate

Continuous knowledge and intent tuning.

Where it lands

Use cases already in production with enterprise clients.

WhatsApp customer service

Full-service customer conversations on the channel customers already use — with handoff to live agents when needed.

In-app conversational commerce

Product discovery, ordering and support in one conversation, tied to CRM and OMS.

Proactive digital outreach

Two-way appointment reminders, payment reminders and service notifications.

Digital-first care navigation

Symptom check, provider search and appointment booking on web and mobile.

Delivered by

Pronix service lines

Runs on

Partner platforms we implement

Explore platform capabilities →

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.

Not sure where to start? Score your organization in 10 minutes.Take the AI Readiness Assessment →

Quick answer

What does Pronix's conversational AI consulting deliver for contact centers?

Pronix builds unified conversational AI virtual agents across web, mobile, WhatsApp and RCS, grounded in enterprise knowledge and integrated with the client's CCaaS and CRM, for contact centers with channel silos or no transactional depth in their existing bots. Delivery is led from the Plainsboro, NJ headquarters, engineered through the Hyderabad delivery center, and supported by London and Dubai for regional coverage.

Last reviewed 2026-08-05

One intent and context model across channels

Rather than separate bots per channel, a unified intent and context layer lets a conversation started on WhatsApp continue seamlessly if it moves to voice or web.

Transactional depth, not FAQ-only

Bots are connected to backend systems so they can complete transactions — order changes, account updates — not just answer static questions.

CCaaS handoff carries full context

When a conversation escalates, the transcript and captured entities pass into the agent desktop so customers do not repeat themselves.

How Conversational AI engagements are bought, supported and staffed.

Most enterprises start with an assessment, move into a fixed-scope build, keep it running under managed support, and add conversational AI engineers and dialog designers where their own team is short. All four can run together under one commercial agreement.

Assessment and roadmap
A bounded Conversational AI assessment: current-state review, prioritized use cases, target architecture, business case and a sequenced delivery roadmap.
Fixed price · 2–4 weeks typical
Fixed-scope build
A defined Conversational AI implementation — architecture, build, integration, testing, evaluation and a documented production release against agreed acceptance criteria.
Fixed price · 8–16 weeks typical
Managed run and support
Monthly operations for Conversational AI in production: release management, integration monitoring, configuration changes, model and agent evaluation and incident response under one SLA.
Monthly service tier · 24×7 coverage available
Staff augmentation
Conversational AI engineers and dialog designers, solution architects and delivery leads embedded in your team, reporting to your delivery manager.
Monthly per person · typically live in 2–4 weeks

Where Conversational AI delivery happens

Programs are led from our Plainsboro, New Jersey headquarters and delivered with our Hyderabad global delivery center, plus London and Dubai for EMEA and Middle East clients.

Support coverage

Business-hours support in your time zone as standard, follow-the-sun 24×7 for production contact center and agentic workloads, with named escalation and monthly service reviews.

Get a Conversational AI scope and price Hire conversational AI engineers and dialog designers

In depth

How conversational AI consulting, implementation and integration fit together on a single intent model.

Conversational AI implementation

Conversational AI implementation covers intent taxonomy, dialog and disambiguation design, knowledge grounding, transactional flows, escalation and analytics. One intent model serves every digital channel, so a change to a billing flow ships everywhere at once instead of being rebuilt per bot.

Single intent model across all channels
Grounded answers with citations and entitlements
Transactional flows into systems of record

Conversational AI integration

Conversational AI integration is where most bots fail: identity, CRM context, order and case systems, knowledge repositories and live-agent handoff. We wire authenticated context into every conversation and pass full transcript and entities on escalation so nothing is repeated.

Authenticated identity and CRM context
Order, case, billing and knowledge connectors
Context-preserving handoff to live agents

AI chatbot consulting

AI chatbot consulting begins with an honest audit of the bots you already have: containment by intent, abandonment points, unanswered questions and knowledge gaps. The output is a remediation plan that usually retires more flows than it adds — then a build plan for the intents worth automating.

Containment and abandonment audit
Knowledge gap and coverage analysis
Retire, rebuild or extend recommendations

Choosing a conversational AI consulting company

A conversational AI consulting company should be accountable for outcomes after launch. We publish containment, resolution and CSAT targets, run regression and safety evals on every release, and operate the assistant under an SLA with monthly tuning cycles.

Published containment and CSAT targets
Regression and safety evals per release
Managed tuning under an operating SLA

Submit a project brief

Scoping a Conversational AI programme? Send us the brief.

Four fields. Tell us the outcome and timeline and a delivery lead for this area replies with indicative scope, team shape and commercial options.

solutionConversational AI — routed to this team

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Where this fits in our practice

Frequently asked

Questions buyers ask us first.

What does conversational AI consulting include?: Bot and channel audit, intent taxonomy, dialog and knowledge design, platform selection, integration architecture, build, evaluation and post-launch tuning.
How long does conversational AI implementation take?: A first channel with a focused intent set typically goes live in 6–10 weeks; additional channels reuse the same intent model and ship considerably faster.
What makes conversational AI integration difficult?: Identity, entitlement-aware knowledge and live-agent handoff. Without authenticated CRM context, assistants can answer questions but cannot resolve them.
Do you offer AI chatbot consulting for bots we already built?: Yes. We audit containment, abandonment and knowledge coverage, then recommend which flows to retire, rebuild or extend before adding anything new.
Which conversational AI platforms do you work with?: Kore.ai, Google Dialogflow CX and CCAI, Microsoft Copilot Studio, IBM watsonx Assistant, Amazon Lex and the native assistants in Genesys, NICE and Five9.
How is a conversational AI engagement priced and what drives cost?: We price a fixed-fee assessment and design phase, a milestone-based build against agreed intents and channels, and a monthly managed-run fee once live, plus optional staff augmentation billed per person per month. Cost is driven by the number of channels, intents and systems-of-record integrations rather than the AI models themselves.
How long does it take to reach a first production release?: A first channel with a focused intent set typically reaches production in 6 to 10 weeks, with additional channels shipping faster because they reuse the same intent model, knowledge layer and CRM integration.
Which CCaaS platforms does conversational AI integrate with and how do we choose?: We integrate conversational AI with Amazon Connect, Genesys Cloud CX, NICE CXone, Five9, Google CCAI and Kore.ai for live-agent handoff. Platform choice follows your existing CCaaS and CRM investment and how much native bot capability that platform already provides.
What does managed support for conversational AI include?: Managed support covers intent and knowledge tuning, containment and abandonment monitoring, regression and safety evaluation on every release, and incident response under a documented SLA, with business-hours coverage as standard and 24x7 coverage available.
What does certified conversational AI talent cost, notice period and delivery locations?: Certified conversational AI engineers and dialog designers are billed at a monthly per-person rate with a standard notice period for ramp-down. Delivery is led from our Plainsboro, NJ headquarters, staffed from our Hyderabad global delivery center, plus London and Dubai for regional coverage.

How we work

Every CX and contact center program runs through one of four engagement models — advisory, implementation, managed operations or embedded pods.

Strategy & advisory Implementation Managed services Talent pods All engagement models →

Who we are

pronix.ai is the AI & CX systems integrator practice of Pronix Inc.

One accountable delivery model: US-based architecture and program leadership with global engineering pods running 24×7 build, cutover and hypercare.

Founded: 2010 · Pronix Inc
Headquarters: 666 Plainsboro Rd, Suite 1361, Plainsboro, NJ 08536
Delivery centers: United States · India (Hyderabad) · EMEA
Engagement model: Fixed-scope implementation, managed run, staff augmentation and T&M Agile Teams.

Certifications

AWS Certified (Solutions Architect, Developer)
Amazon Connect specialty
Genesys Cloud CX certified
NICE CXone certified
Salesforce certified (Service Cloud, Agentforce)
Microsoft Azure AI certified

Security questionnaires, controls documentation and named client references are available under NDA. More about Pronix Inc →

Next step

Book a working session with our conversational ai team.

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

Schedule the session →Read the playbook

Conversational AI implementation for contact centers.

Measurable outcomes, not slideware.

Digital bots without context are a modern IVR.

One conversational layer across every digital channel.

The conversational AI reference architecture.

Customer channels

NLU & dialog orchestration

Knowledge & fulfilment

Escalation & agent handoff

CCaaS & systems of record

What is conversational AI?

Designing a conversational AI program in five steps

Rank intents by value

Choose the channel order

Ground answers

Define escalation

Operate and expand