No Matter Where You Start, We Know How To Get You There
We're expert guides with battle-tested methodologies from years of enterprise contact center AI implementations. There's more than one path, but we can always find the right route for your unique destination—and we know how to build resilience into your plan so obstacles don't derail your project.
The 5-Phase Migration Framework
AI Readiness
Assessment
4-6 weeks
AI-Native
Strategic Planning
3-4 weeks
Controlled
AI Validation
2-3 weeks
Phased
AI Deployment
3+ months
Full-Scale
AI Operations
Ongoing
Phase 1:
AI Readiness
Assessment
Understand Your Starting Point for AI Transformation
We evaluate your technical, organizational, and UX foundation to establish the right starting point for your transformation. This comprehensive assessment covers your current infrastructure, team capabilities, and customer experience baseline—ensuring we understand your unique landscape before charting the route forward.
What You Get:
- Conversation Data Analysis: Review of call transcripts, chat logs, and agent notes to identify intents, entities, and training data opportunities
- Data Structure Evaluation: Assessment of CRM integrations, knowledge bases, API access, and data quality for AI consumption
- AI Use Case Identification: Determination of which interactions benefit from conversational AI, agent assist, or rule-based automation
- Governance Framework Setup: Establishment of AI oversight committee, risk management protocols, and accountability structure
- Baseline Metrics: Current containment rates, handle times, customer satisfaction, and intent coverage gaps
Phase 2:
AI-Native
Strategic Planning
Design Your Intelligent Automation Architecture
We don't just replicate your IVR menu in conversational form—we reconceive customer interactions to leverage AI capabilities that weren't previously possible. This phase transforms rigid phone trees into natural conversations and empowers agents with real-time AI assistance.
What You Get:
- Intent Architecture & Conversation Design: Mapping of legacy IVR paths to AI-powered conversation flows optimized for natural language
- AI Training Data Strategy: Plan for data collection, labeling, model training, and knowledge base restructuring for AI consumption
- Technology & Integration Blueprint: AI platform selection (LLM providers, conversation AI, vector databases) and integration architecture with existing systems
- AI Governance Policies: Response guidelines, escalation rules, compliance requirements, and ethical AI principles
- Change Management Plan: Redesigned QA processes, evolved roles & responsibilities, and agent training roadmap for AI-augmented workflows
- Prioritized Roadmap: Risk-mitigated timeline with resource requirements and AI-specific success metrics
Phase 3:
Controlled AI
Validation
Prove AI Performance Before Customer Impact
We test AI capabilities in controlled environments to validate accuracy, safety, and business value. This phase identifies risks, optimizes confidence thresholds, and ensures your AI represents your brand accurately before any customer exposure.
What You Get:
- Shadow Mode Testing: AI runs parallel to legacy IVR to compare performance without customer risk
- AI Safety Validation: Testing for response accuracy, brand alignment, hallucination prevention, and compliance adherence
- Confidence Threshold Optimization: Tuning when AI responds autonomously vs. escalates to human agents
- Agent Assist Pilot: Testing AI tools that provide real-time guidance, knowledge retrieval, and next-best-action recommendations during live interactions
- Refined Business Case: Real performance data validating ROI assumptions and informing rollout strategy
Phase 4:
Phased
AI Deployment
Scale Intelligence with Continuous Learning
We implement AI gradually—expanding from simple intents to complex conversations, from customer-facing automation to comprehensive agent augmentation. Each phase includes model retraining based on real interactions, ensuring continuous improvement.
What You Get:
- Progressive Rollout: Systematic expansion from low-risk intents to complex use cases, maintaining service quality throughout
- Model Performance Monitoring: Real-time tracking of intent accuracy, user sentiment, containment rates, and AI confidence distributions
- Continuous Model Training: Regular refinement of AI based on customer interactions, edge cases, and agent feedback
- Process Transformation: Implementation of AI-informed QA processes, evolved agent workflows, and new performance metrics
- Agent Enablement: Ongoing training as AI capabilities expand and roles shift toward high-value customer interactions
Phase 5:
Full-Scale AI
Operations
Achieve Sustained Competitive Advantage
Your AI transformation becomes a living capability—not a one-time project. We establish governance processes for ongoing model monitoring, bias detection, and strategic expansion of AI capabilities across channels and use cases.
What You Get:
- Enterprise-Wide AI Deployment: Full implementation of conversational AI and agent assist across your contact center
- AI Governance Operations: Ongoing audits, bias detection, performance reviews, and compliance monitoring
- Omnichannel AI Expansion: Extension of AI capabilities across voice, chat, email, and emerging channels
- Generative AI Evolution: Strategic movement from scripted responses to dynamic content generation where appropriate
- Continuous Optimization: Regular model updates, intent expansion, and process refinement based on evolving business needs