How I use AI in revenue systems.
Practical AI integrated into strategy, not bolted on as an afterthought.
AI is a method, not a product. Every engagement I deliver, whether Fractional Chief Growth Officer, RevOps Architecture, or MarTech Advisory, is AI-native by design. I don't sell AI services. I build revenue systems where AI is the infrastructure, not the pitch.
AI Agents
Autonomous systems that work while you sleep.
- Intelligent customer support routing that resolves before escalation
- Compliance monitoring agents tracking regulatory changes in real-time
- Competitive intelligence agents scanning markets, press, and filings
- Internal knowledge agents answering team questions from your own data
AI-powered Automations
Eliminate repetitive work. Redeploy human capacity.
- Lead scoring and qualification sequences driven by behavioral data
- Multi-channel outreach sequences with dynamic personalization
- CRM data enrichment and hygiene automation
- Reporting pipelines that generate Board-ready dashboards from raw data
AI-augmented Workflows
Your teams, amplified. Not replaced.
- Sales enablement copilots generating proposals, briefs, and battle cards
- Content production workflows: research, draft, review, publish
- Due diligence acceleration for M&A, vendor selection, and partnerships
- Executive briefing systems synthesizing data into decision-ready insights
Built different.
Three principles that separate my AI approach from the noise.
Principle #1
Compliance-first
Every AI system is designed with GDPR, AI Act, and industry-specific regulations baked in. Not retrofitted. 14+ years in regulated Financial Services environments.
Principle #2
Practical, not experimental
Applied AI, production-ready tools and workflows. No bleeding-edge experiments with your revenue. If it doesn't move a metric, it doesn't ship.
Principle #3
Human oversight, always
AI handles the repetitive and data-heavy. Your team handles judgment, relationships, and strategy. The goal is amplification, not replacement.