Three disciplines.
One operator.
AI strategy, M&A advisory, and applied AI execution — delivered by one operator with 15 years in the chair and $4B+ in deals closed.
AI Strategy
Where AI actually creates value.
Board-level clarity on where to invest, where to partner, and where to stay out — without the vendor theater. Most AI consultants hand you a framework. I hand you a decision.
Coming from Google, Intuit, and Philips, I’ve sat at the table where the budget gets allocated. I know what boards want to hear — and what they need to hear instead.
Explore engagement models →Deliverables
A structured assessment of your current AI stack, team capabilities, and data infrastructure. Output: a prioritized gap analysis and a 90-day action map tied to real business outcomes — not a slide deck of best practices.
A decision framework grounded in your cost structure, timeline, IP risk, and team. Cuts through vendor pitches by naming which decisions belong in-house and which belong in a contract — with the numbers to back each call.
Market sizing and competitive analysis built for AI-era dynamics — where moats shift in months, not years. I track 800+ AI companies continuously. Your TAM model will reflect the actual competitive landscape, not a stale analyst report.
A compelling, technically credible narrative that explains your AI strategy to a board or investor audience. These aren’t boilerplate decks — they’re customized to your business model, your competitive position, and the specific questions your board will ask.
M&A Advisory
$4B+ in deals.
Now rebuilt for AI.
Targeting, diligence, structuring, and integration — the full M&A stack, AI-native. I’ve done this at scale across healthcare, fintech, enterprise software, and infrastructure.
Most advisors hand you a CIM. I hand you a sourcing engine, a diligence thesis, and a post-close playbook that actually gets executed.
Explore engagement models →Deliverables
A continuously updated acquisition pipeline built against your specific strategic thesis. I use AI Radar — my own 800+ company tracking database — to surface non-obvious targets before they show up in banker books.
A structured diligence framework that goes beyond financials. I assess model architecture, proprietary data assets, team dependency risk, and whether the technical moat is real or a demo. Output is a scored risk matrix with deal-breakers clearly flagged.
Financial modeling that ties AI-specific synergies (compute consolidation, model reuse, data network effects) to real EBITDA impact. I build the model and the narrative — from LOI through board approval.
Most AI acquisitions fail in the first 90 days of integration. I build Day 1 playbooks that address the highest-risk failure modes: talent retention, model migration, data ownership, and customer communication — in a sequence that actually holds.
Applied AI Tools
I don’t just advise.
I ship.
Six production tools. 800+ AI companies tracked in real-time. An advisor who has actually built and deployed the systems they’re recommending.
These aren’t demos — they’re tools I use in my own advisory workflow. When a client asks if something is feasible, I’ve already built the answer.
See all tools →Production Tools
A live database tracking 800+ AI companies across funding, team, product, and competitive signals. Used for M&A sourcing, market mapping, and competitive intelligence. Updated continuously. Live demo →
70+ AI research reports, papers, and frameworks curated and indexed for fast retrieval. Covers model architecture, enterprise deployment, and market dynamics. Used as a first-pass research layer before deep diligence. Live demo →
A structured ROI model for enterprise AI projects. Inputs: headcount, compute cost, use case type. Output: 3-year financial model with payback period and sensitivity analysis. Built to survive CFO scrutiny. Live demo →
Real-time geopolitical and commodity signal tracking applied to capital allocation decisions. Monitors Strait of Hormuz traffic, OPEC signals, and macro indicators relevant to energy-adjacent AI investments. Live demo →
How We Work
Three ways to engage.
No retainer requirements for project work. No vendor relationships that skew advice. Structured around your actual decision timeline.
01 — Fractional
Embedded Advisor
A consistent advisory relationship with defined hours per month. Right for companies navigating a multi-phase AI strategy or an active M&A process.
Monthly retainer · 6-month minimum02 — Project
Scoped Engagement
A defined deliverable with a fixed timeline. Right for a board presentation, a diligence sprint, a build-vs-buy decision, or an integration playbook.
Fixed fee · 4–10 week delivery03 — Tools
Tool Licensing
Access to AI Radar, AI Book, AI ROI Calculator, and other production intelligence tools. Right for teams that need ongoing market signal without full advisory.
Per tool or bundle · annual accessOur Process
From first call to decision.
Most engagements move from intake to first deliverable in under two weeks.
Diagnostic Call
30 minutes. I learn your context, decision horizon, and where you’re stuck. No pitch deck, no prep required.
Scoped Proposal
Within 48 hours: a one-page engagement scope with deliverables, timeline, and fee. Take it or leave it — no negotiation theater.
Kick-Off Sprint
We align on the specific question that needs answering and the evidence required. Week one ends with a working hypothesis.
Decision-Ready Deliverable
A document your board or exec team can act on. Not a summary of what we found — a recommendation with the supporting case built in.
Ready to find your
next move?
A 30-minute call is enough to know whether there’s a fit. No pitch. No obligation. Just a direct conversation about your actual situation.