Implementation Guide
From Data Requests to Embedded Intelligence
A step-by-step guide to deploying Breeze AI agents, configuring intelligence workflows, and embedding context where decisions happen.
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UBC requires unified data. AI agents can't provide intelligence if underlying data is fragmented.
Verify UCV and URV are complete. AI needs unified customer and revenue data to surface meaningful patterns.
Identify key decision points where embedded intelligence would change outcomes.
Evaluate organizational readiness to trust and act on AI-powered intelligence.
Critical Dependency
Don't start UBC until UCV + URV Foundations are validated. AI agents need complete data to provide meaningful intelligence.
Deploy the AI agents that will provide embedded intelligence across your operation.
Natural language query interface
30 min
AI-powered support intelligence
25 min
Context-aware content creation
20 min
Pattern-based lead intelligence
20 min
Social monitoring and sentiment intelligence
15 min
Agent Philosophy
AI agents amplify human capability, not replace human judgment. They surface intelligence; people make decisions.
Create automated workflows that surface intelligence at decision points.
Workflows that proactively surface concerning or promising patterns before they become obvious.
Automated context injection into records so intelligence is visible where work happens.
Systematically capture successful approaches so organizational learning compounds.
Intelligence Flow
Pattern Detection → Context Enrichment → Decision Support → Knowledge Capture → Loop
How do you know if it's working? Each milestone has specific validation criteria.
AI agents deployed and functional. Teams can ask questions in natural language and get intelligent answers.
Test: "What customers show similar patterns to ones that churned last quarter?"
Answer should come from Copilot in <30 seconds
Organization trusts and acts on AI insights. Proactive interventions become the norm.
Test: "How many customer issues were addressed proactively this month?"
Should be measurable and trending upward
Intelligence infrastructure enables decisions competitors cannot match. Learning accelerates.
Indicators: Teams cite AI intelligence in decision discussions; new hires productive faster
Sales and success calls with real-time context
Intelligence Needs:
Faster resolution with proven approaches
Intelligence Needs:
Strategic questions answered instantly
Intelligence Needs:
Prioritization Principle
Start with decisions that happen frequently and have measurable impact.
Complete Part 1. Verify data foundation, identify use cases, assess AI readiness.
Complete Part 2. Deploy AI agents for prioritized use cases.
Complete Part 3. Build pattern alerts, context enrichment, knowledge capture.
Complete Part 4. Run validation tests, build organizational trust in AI intelligence.
The interactive playbook guides you through every step with checklists, configuration cards, and validation tests.
Track your progress. Build trust incrementally. Transform decision-making.
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