Fractional AI Leadership

Strategy, architecture, and hands-on building — in the same week, for the same company

Every recommendation I make, I can back up at the terminal.

The range

Boardroom to terminal. I cover the full stack of AI leadership so you don't need three different consultants.

Boardroom

  • AI roadmap & prioritization
  • Build vs. buy analysis
  • Board & investor narratives
  • AI risk & governance framing
  • Vendor & platform evaluation

Technical

  • Architecture review with your CTO
  • Prototype & proof-of-concept builds
  • Model selection & cost optimization
  • MCP integration & tooling design
  • Data pipeline & RAG architecture

Research

  • Feasibility deep-dives before you commit
  • Competitive AI landscape analysis
  • Emerging capability assessment
  • Cost modeling at production scale
  • Technical due diligence
Built, not theorized
Product

InstantContext.ai

Context-seeding platform that turns any business's knowledge into structured AI conversations via QR codes and embeddable widgets.

Product

MeetBri.ai

27,000+ executive interview transcripts powering ICP analysis, message-fit scoring, and language intelligence at a fraction of human research cost.

Advisory

BCC Research

AI Product Advisor. Built VerticalContext.ai — an MCP-powered market intelligence product — and shaped their subscription platform strategy.

Research

MCP Ecosystem

Published research across 420+ MCP servers and 1,400+ tools. Built MCPalign.com for manifest alignment testing. Active since the protocol's launch.

Platform

AiBBS

Async human-AI collaboration workspace where artifacts stay alive. MCP-native. Reference implementation for the ICE-T pattern.

Product

LitAi

Legal AI drafting platform with multi-tier citation validation achieving 99.988% accuracy across authority, temporal, and ecological checks.

How it works

Flexible engagements designed around what you actually need — not a packaged consulting playbook.

Project

Scoped Engagement

A focused project to answer a hard question or build something specific. Should we build this? What's the right architecture? Here's a working prototype that proves it.

  • →Typically 2-8 weeks
  • →Feasibility research + architecture
  • →Working prototype or proof of concept
  • →Decision-ready deliverable for leadership
  • →Handoff documentation for your team
Most common
Ongoing

Fractional CAIO

Embedded AI leadership on a part-time basis. I join your leadership rhythm, work with your technical team, and own the AI roadmap.

  • →1-2 days per week
  • →Executive team + CTO collaboration
  • →Roadmap ownership & prioritization
  • →Hands-on prototype & architecture work
  • →Quarterly board-ready reporting

Let’s figure out what AI
actually looks like for you

No pitch deck. Just a conversation about where you are, what you're trying to do, and whether I can help.