Customer Support Platform (like Zendesk + AI)

• Intent Layer: Customer wants to "resolve billing dispute quickly"
• Reasoning Layer: AI analyzes ticket content, customer history, sentiment, and similar cases to determine this needs immediate escalation + proactive credit
• Orchestration Layer: AI routes to billing specialist, pre-populates case details, suggests resolution steps, schedules follow-up
• Data Synthesis Layer: Combines structured data (billing records, SLA status) + unstructured (email tone, chat history, social media mentions)
• Execution Layer: Actual credit processing, SLA tracking, and compliance logging remain deterministic

Sales Intelligence Platform (like Salesforce + AI)

• Intent Layer: Sales rep wants to "close this enterprise deal faster"
• Reasoning Layer: AI identifies deal risks by analyzing proposal language, competitor mentions, stakeholder engagement patterns, and timing signals
• Orchestration Layer: Suggests specific actions (which decision-maker to contact next), generates personalized content, schedules optimal follow-up timing
• Data Synthesis Layer: CRM data + email interactions + calendar patterns + industry news + competitive intelligence
• Execution Layer: Actual email sending, calendar booking, opportunity stage updates follow traditional workflows

Domain-AI Integration Matrix Examples

Legal Tech Platform

• High-domain, Low-AI: Regulatory compliance checks (needs legal expertise, but rules are deterministic)
• High-domain, High-AI: Contract risk assessment (legal expertise guides what to look for, AI finds patterns across thousands of contracts)
• Low-domain, High-AI: Document formatting and organization (generic AI capability)
• Emerging Hybrid: Predictive case outcome modeling (combines legal reasoning with pattern recognition from case databases)

Financial Planning Software

• High-domain, Low-AI: Tax calculation engines (complex rules, but deterministic)