Omni-CCAI – Intelligent Guided Selling & CPQ Orchestrator
Agentic Product Configuration, Dynamic Pricing & Generative Upsell for MedTech
Omni-CCAI is an enterprise-grade sales orchestrator that transforms traditional "cost-center" chatbots into revenue-generating engines. Built on Dialogflow CX and Vertex AI, it automates complex, attribute-based configuration for medical imaging suites—enforcing clinical dependencies, calculating real-time dynamic pricing, and leveraging Gemini 1.5 Flash for hyper-personalized upsell reasoning. By bridging the gap between unstructured customer intent and structured CPQ logic, it reduces configuration errors by 40% and boosts Average Order Value (AOV) through context-aware cross-selling.
Google Cloud Integration Highlights
- • Dialogflow CX for state-machine sales orchestration
- • Vertex AI (Gemini 1.5) for generative upsell reasoning
- • Cloud Functions for the "Brain" (CPQ Rules & Pricing)
- • BigQuery for conversation analytics & conversion tracking
- • Firestore for real-time session state & quote persistence
- • Cloud KMS for field-level encryption of quote PII
Executive Summary: The Conversational CPQ Edge
Vision: Eliminating sales friction in MedTech by transforming complex hardware specs into deterministic, compliant quotes through an AI-native sales pipeline.
1. The Strategic Imperative
Traditional CPQ systems require expert training. Omni-CCAI democratizes this knowledge, allowing non-expert channels to handle $2M+ configurations with 100% safety compliance.
2. The Solution: AI-Native CPQ
A unified platform that uses Generative AI for natural engagement and Deterministic Webhooks for the "Golden Rules" of clinical configuration.
Enterprise Architecture (TOGAF ADM Deep Dive)
Phase A/B: Vision & Business (Capability Map)
Mapping user intent to clinical-grade CPQ logic gates.
Phase C: Information Systems (State & Data Flow)
Phase D: Technology (Serverless Stack)
6. Business Strategy: Mastering MedTech Complexity
6.1 Strategic Value Proposition
| Value Pillar | Operational Outcome |
|---|---|
| Revenue Growth | Proactive upsells driving 15% AOV uplift. |
| Risk Mitigation | 100% compliance with clinical safety rules (e.g. Quench Pipes). |
6.2 Regulatory Strategy
Built with HIPAA-ready GCP constructs, ensuring PII in quotes is encrypted via Cloud KMS and session data is ephemeral.
6.3 Product Catalog Master Data (Ground Truth)
| Modality | Base Price | Mandatory Add-on |
|---|---|---|
| MRI | $1,800,000 | Quench Pipe (+$80k) |
| CT Scanner | $1,200,000 | Radiation Shielding (+$150k) |
6.4 Current State
6.5 Future State
6.6 Change Management (SAFe ART Flow)
Leveraging an Agile Release Train to synchronize MedTech compliance officers with AI Engineering squads.
6.7 Target Value Stream
7. User Centric Design
7.1 User Personas
B2B Buyer
Wants clinical self-service.
Sales Rep
Needs a 24/7 quoting assistant.
Controller
Ensures no pricing leakage.
7.2 Requirements (MoSCoW)
| Requirement | Priority |
|---|---|
| Attribute-based MRI Configuration | Must |
| Generative Gemini Upsell Reasoning | Should |
8. Technical Rollout Roadmap
| PI | Focus | Deliverable |
|---|---|---|
| PI-1 | Configuration | Dialogflow CX State Machine |
| PI-2 | Optimization | Gemini 1.5 Reasoning Layer |
9. Multi-Agent Reasoning Chain: "Logic Swarm"
9.1 The Autonomous Workforce
- The Architect: Dialogflow CX (State & Intent)
- The Brain: Python Webhook (Rule Enforcement)
- The Influencer: Gemini 1.5 (Generative Social Proof)
9.2 The "Reasoning Trace" (conversational proof)
User: "Configure a 3T MRI."
[Action]: Automatically upgrade tier and suggest 'AI Diagnostics'.
Agent: "Excellent. I've upgraded you to the Premium Tier to support 3T. Would you like to add AI Diagnostics used by 82% of similar facilities?"
9.3 Decision Matrix & Conflict Resolution
Priority 1: Clinical Compatibility (Safety Override)
Priority 2: Hardware Dependencies
Priority 3: Revenue Optimization (Upsell)
10. Intelligence Platform: Data Fabric
10.1 Unified Intelligence Stack Architecture
Stateless orchestration via Cloud Functions ensures sub-second latency for complex rule evaluation.
10.2 Semantic Mapping
Translating fuzzy user needs (e.g. "I need fast imaging") into structured attributes (256-slice CT).
10.3 Conversational Telemetry
Pushing every recommendation event to BigQuery for conversion analytics.
11. Model Lifecycle (MLE)
Continuous prompt tuning for Gemini 1.5 ensures upsell reasoning remains objective and trust-based.
12. Cloud Infrastructure & Multi-Region SRE
13. AI Governance & Regulatory Compliance
Immutable logging of every rule trigger ensures that conversational sales are fully auditable for MedTech standards.
14. Impact & Outcomes: Financial Transformation
- 📉 40% Reduction in configuration errors
- 💰 15% Boost in Average Order Value
- 🛡️ 100% Audit trail for safety rules
- ⚡ Instant quote generation