Conversational AI consulting and implementation.
Pronix is a conversational AI consulting and implementation partner — platform selection across Kore.ai, Google Dialogflow CX, IBM Watsonx and Salesforce Agentforce, then production delivery of voice, chat and email assistants and agents with evaluation and guardrails built in.
One team for strategy, platform selection, build and managed operations — so conversational AI doesn't stall between the pilot and the contact center.
Most conversational AI programs stall on platform fit and evals.
The blockers are rarely the model. They are platform fit for your CRM and CCaaS estate, unclear deployment patterns across voice, chat and email, missing evaluation harnesses and a migration path off legacy IVR that respects live traffic.
- Assistants vs agentsTeams pick one paradigm and get stuck. We design a portfolio — scoped assistants for containment, agents for end-to-end resolution — under one governance model.
- Platform selection is a decision, not a preferenceKore.ai, Dialogflow CX, Watsonx and Agentforce each win in different estates. We score them against your intents, data, channels and total cost before you commit.
- No production evaluation practiceWithout golden sets, drift monitoring and human-in-the-loop review, quality regressions surface as complaints. We instrument first, ship second.
Everything needed to ship conversational AI to production.
Assistants and agents, platform-native, evaluated in production, integrated with your CCaaS and CRM.
Portfolio design across scoped assistants (FAQ, self-service, forms) and agents (transactional, tool-using) with clear ownership and escalation.
Structured scoring across Kore.ai XO / Agent Platform, Google Dialogflow CX, IBM Watsonx Assistant and Salesforce Agentforce — mapped to your top intents, data and channels.
Low-latency voice agents on Amazon Connect, Genesys, NICE, Five9 and Google CCAI — with barge-in, DTMF, warm handoff and CRM screen-pop.
Web, in-app, WhatsApp, RCS, SMS, Messenger and Teams — unified intents, context and knowledge across channels.
Inbound email classification, extraction, response drafting and case routing — integrated with Salesforce, Dynamics, ServiceNow and Zendesk.
Golden sets, offline/online evals, PII redaction, prompt-injection defense, toxicity detection, drift monitoring and human-in-the-loop review.
Assess, map and rebuild legacy IVR and first-gen bots into modern conversational AI with regression parity and canary cutover per queue and language.
Per-conversation, per-minute, per-resolution and platform-license modeling — with total-cost-of-ownership across build, run and managed operations.
Every conversation — voice or digital — runs the same six-stage loop.
Detect → Authenticate → Retrieve → Act → Resolve → Summarize. Each stage has explicit controls so voice AI, agent assist and automated QA plug into one operating model.
Identify intent across voice and digital with unified NLU, sentiment and language detection.
- Intent model
- Language detect
- Sentiment
- Channel context
Verify the customer with voice biometrics, OTP or federated SSO before any transaction.
- Voice biometrics
- OTP / step-up
- SSO / KYC
- Consent capture
Ground the conversation in governed knowledge and system-of-record data with citation and access control.
- Governed RAG
- CRM lookup
- Order / policy data
- Citations
Execute transactions through scoped tool connectors — billing, scheduling, order and case actions.
- Scoped tools
- Per-action auth
- Idempotency
- Audit trail
Complete the intent, or warm-transfer to a live agent with full context, transcript and next-best-action.
- Warm handoff
- Context payload
- NBA to agent
- Screen pop
Auto-summarize, code the disposition, and score 100% of interactions with automated quality and compliance detection.
- Auto-summary
- Disposition
- Automated QA
- Compliance flags
One policy layer across every stage — voice and digital.
Consent, redaction, residency and human oversight are enforced inside the conversation runtime — not in a separate ops process.
- PII redaction & masking
- Consent & recording rules
- Regional data residency
- Real-time policy guardrails
- Human-in-the-loop escalation
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.
Intent inventory, channel map, data readiness, platform fit.
Kore.ai / Dialogflow CX / Watsonx / Agentforce scoring.
Assistant vs agent portfolio, guardrails, evaluation harness.
One high-volume intent, one channel, live evals from day one.
Production build, CCaaS + CRM integration, canary rollout.
Managed ops, weekly eval gates, tuning and new use cases.
Use cases already in production with enterprise clients.
Authenticated, transactional voice agent on Amazon Connect / Genesys / NICE / Google CCAI that finishes the job and hands off with context.
One assistant across web, WhatsApp, in-app and RCS — with unified intent, session state and knowledge.
Rebuild a legacy IVR or first-gen bot on Kore.ai, Dialogflow CX, Watsonx or Agentforce with 99%+ regression parity.
Automated classification, extraction and drafting for inbound email — routed into Salesforce, Dynamics or ServiceNow.
A 3–4 week engagement that scores Kore.ai, Dialogflow CX, Watsonx and Agentforce against your intents, data and channels.
Industries where this ships fastest
- Financial Services
- Insurance
- Healthcare Providers
- Health Payers
- Retail & Ecommerce
- BPO
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.
Questions buyers ask us first.
- What is the difference between a conversational AI assistant and an AI agent?
- Assistants answer, retrieve and route inside a scripted or intent-driven flow. Agents reason, use tools and complete transactions in your systems of record with authorization, evals and audit. Most enterprises need both — assistants for scoped conversations, agents for end-to-end resolution.
- How do you pick between Kore.ai, Dialogflow CX, Watsonx and Agentforce?
- By fit — CRM alignment, contact-center estate, model portability, governance, vertical accelerators and total cost. We run a platform-selection sprint that scores each against your top intents, data sources and target channels before you commit.
- Can we migrate off a legacy IVR without disrupting live traffic?
- Yes. We run parallel deployment with regression parity gates and canary cutover per queue and language, so nothing breaks and CSAT and containment are measured against the legacy baseline.
- How do you evaluate conversational AI quality in production?
- Golden sets, offline and online evals, prompt/response scoring, PII and toxicity detection, drift monitoring and human-in-the-loop review — operated as a program with weekly gates, not a one-off script.
- What does a typical engagement cost and how long does it take?
- Time-and-materials or fixed-fee per phase. A first production assistant on a chosen platform typically ships in 6–10 weeks; voice deployments and multi-language rollouts run 10–16 weeks. Managed operations are a monthly subscription tied to volume and channels.
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.