AI Strategy

AI That Delivers

Strategy, execution, and accountability for teams racing to lead.

The Playbook

Signal emerging from noise, representing strategic clarity

AI Strategy

Clarity over hype. Define where AI creates real competitive advantage, prioritize ruthlessly, and align every investment to strategic outcomes.

  • AI Strategy & Roadmapping
  • Investment Priority Alignment
Continuous iteration loop, representing adaptive product development

Product Strategy

Feasibility meets market. Evaluate viability, shape the roadmap, and ship AI products that actually work, from concept through GTM.

  • AI Product Strategy
  • GenAI Feasibility Assessments
Nested system layers, representing governance as infrastructure

Ethical AI & Governance

Accountability by design. Build governance frameworks, deployment pipelines, and responsible AI practices that stakeholders defend and regulators trust.

  • Ethical AI & Governance
  • MLOps & Deployment Strategy

Point of View

Earned through 15 years of building, shipping, and watching things fail.

Most AI initiatives fail because of organizational problems, not technical ones. The model works fine. The team doesn’t know what to do with it.

The fastest way to waste money on AI is to skip the strategy phase. Jumping straight to tools and vendors is how you end up with expensive demos that never reach production.

If your AI vendor can’t explain their approach in plain language, they don’t have one. Complexity is not a sign of sophistication. It’s usually a sign of confusion.

The goal of every engagement is to make the client self-sufficient. If you still need me six months later, I haven’t done my job.

How We Work

01

Find the Signal

Map your AI landscape, data readiness, and organizational gaps. Cut through vendor noise and separate real capability from marketing claims.

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02

Prioritize Ruthlessly

Build a focused roadmap with clear milestones, ownership, and every investment tied to outcomes. Kill the projects that sound exciting but won’t move the needle.

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03

Ship What Works

Hands-on delivery. Product strategy, feasibility assessments, and MLOps pipelines, whatever the roadmap demands. Speed over perfection, but never recklessness.

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04

Transfer Ownership

Knowledge transfer, governance frameworks, and operational playbooks so your team sustains momentum independently. The goal is independence, not dependency.

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The Signal Test

Five questions that separate AI initiatives worth pursuing from expensive distractions. If you can’t answer all five, you’re not ready to build.

01

What decision does this improve?

AI that doesn’t change a decision or action is a science project. Name the specific decision, who makes it, and how it changes.

02

Is the data available today?

Not “could we collect it” or “we’re working on it.” Is the data accessible, clean enough, and governed right now? If not, that’s the real project.

03

Who owns this after launch?

If the answer is “the vendor” or “we’ll figure it out,” stop. Every AI system needs an internal owner with the authority and skill to maintain it.

04

What happens when it’s wrong?

Every model is wrong sometimes. Define the blast radius. A bad product recommendation is annoying. A bad medical diagnosis is catastrophic. Design accordingly.

05

Can you measure success in 90 days?

If the value is “long-term” or “strategic,” you don’t have a metric yet. Define a leading indicator you can measure within one quarter.

Building Blocks

Every engagement draws on major LLM platforms, AI frameworks, and proven ML tooling. Grounded in product strategy, MLOps discipline, and hands-on delivery.

LLM Platforms
OpenAI Anthropic Google Gemini Meta Llama xAI Groq
Development & Tooling
Vercel AI SDK Azure AI Foundry Next.js Cognigy MCP
ML & Data Science
Hugging Face PyTorch scikit-learn
Techniques
RAG Prompt Engineering Context Engineering ReAct Agentic AI

What People Say

“Scott is an excellent communicator, always asking thoughtful questions about how to improve the organization. He asked questions to get me to think bigger, or smaller, as the situation directed. Rather than provide a one-time answer, he always took time to help me train myself.”

Kelly Wasilewski Lead Tech Support Specialist, Honeywell

“He is innovative, dedicated and highly intelligent. I challenged Scott with multiple issues and problems that required a solution to enable the business to both grow and ensure standardization across multiple platforms. Scott solved all the challenges and brought innovative business improvements to the table.”

Mark Halstead MBA, MBOM USN(Ret) Area Manager, Schneider Electric

“I have been in the industry for 44 years and have never been supported by a CMMS like the one created by Scott. His frontline experience and his desire to bring value to his Customer makes him a great asset.”

Michael Burgner National Sales Executive, Concentric

Ready to Move?

The race rewards speed and clarity. Share your AI challenge and let’s figure out where you stand and where you should be.

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