AI Consulting
Turn AI opportunities into working systems.
I help companies identify where AI can create meaningful business value, design the systems around those opportunities, and get useful AI into production.
My work spans AI strategy, data, architecture, agents, automation, evaluation, and implementation. I can work with executives on what should be built, then go deep with product, data, and engineering teams on how to make it work.
Where I Usually Get Involved
- You know AI could materially improve your operations, but you are not sure where to start.
- You have several AI ideas and need to determine which ones are worth building.
- You have a prototype that needs to become a reliable production system.
- You want agents or AI automation embedded into a real workflow.
- Your data or systems are preventing AI initiatives from moving forward.
- Your team is building with AI but lacks experienced technical leadership.
- You need to know whether an AI investment, architecture, or vendor approach actually makes sense.
Find. Build. Scale.
Find
Identify and prioritize the AI opportunities actually worth pursuing.
Build
Turn the best opportunity into a working, production-grade system.
Scale
Expand the capability and put the leadership, architecture, and operating model in place around it.
AI Opportunity & Automation Assessment
Find the highest-value AI opportunity actually worth building.
A focused engagement to identify and prioritize the 3–5 highest-value AI and automation opportunities in your operations, workflows, and data — and determine what is realistically buildable given your systems and constraints.
What's included
The engagement typically includes:
- Review of key workflows, systems, and data
- Stakeholder interviews and working sessions
- 3–5 highest-value AI and automation opportunities, prioritized by business value, feasibility, complexity, risk, and time-to-value
- Data and technical readiness assessment, plus architectural considerations
- A concrete implementation roadmap for the best opportunity, and an executive readout
You leave with a short list of the opportunities actually worth pursuing, a clear read on what's realistically buildable, and a roadmap for the strongest one.
Best for: organizations that know there is AI opportunity in their business but need a sharp, fast way to identify the few worth acting on now.
Typical range: $6K–$12K.
AI Production Sprint
Take one high-value AI use case from idea to a working system.
A focused engagement to design, build, test, and operationalize one high-value AI capability — designed around real operating conditions, not a demo.
What's included
Examples include AI agents, workflow automation, internal copilots, knowledge systems, intelligent document workflows, natural-language analytics, decision-support systems, and AI evaluation and monitoring systems.
Depending on scope, the work can include:
- Use-case definition, workflow and system design, and architecture
- Data integration and model/agent design
- Application or workflow implementation
- Evaluation framework, testing, and human-in-the-loop controls where appropriate
- Observability, deployment, documentation, and handoff/training
Best for: teams that have a valuable AI use case but need experienced technical leadership and hands-on implementation to get it working in the real world.
Typically 4–8 weeks, depending on scope.
Typical range: $20K–$50K+.
Custom AI Systems
Build larger AI, data, and automation systems around important business workflows.
For work broader than a single sprint. My strength here isn't shipping an LLM feature — it's designing complete systems that combine AI models, traditional software, data, workflow logic, evaluation, feedback, monitoring, and human judgment.
What's included
- Agentic systems: AI agents that research, analyze, monitor, coordinate, or execute work across tools and systems.
- Knowledge systems: turn fragmented documents, conversations, or institutional knowledge into useful AI-powered organizational systems.
- Data intelligence: systems that integrate, monitor, analyze, enrich, clean, or reason over operational data.
- Decision intelligence: systems that combine models, business logic, data, AI, and human judgment to support better decisions.
- Workflow automation: replace repetitive manual knowledge work with governed, AI-enabled workflows.
- Evaluation & governance: the evaluation, monitoring, feedback loops, and controls reliable production AI requires.
See examples of this kind of work in Projects — including production data platforms, catalog and enrichment systems, and forecasting engines.
Best for: organizations with a larger AI or data opportunity that requires custom system design, integration, and implementation.
Projects typically start around $30K. Larger engagements are scoped individually.
Fractional AI & Data Leadership
Senior AI and data leadership without hiring another full-time executive.
For organizations that already have AI initiatives underway but lack the senior technical leadership to prioritize work, make architecture decisions, lead teams, evaluate technical proposals, and get projects across the finish line.
What's included
I work between the executive team, product, engineering, data, and AI/ML teams. Responsibilities can include:
- AI and data roadmap ownership, and architecture review
- Technical leadership, project prioritization, and team leadership/mentoring
- Vendor evaluation, AI governance, and evaluation strategy
- Data architecture and production readiness
- Executive communication and implementation oversight
Best for: companies investing seriously in AI that need experienced leadership to connect strategy, architecture, data, and execution.
Typical range: $15K–$25K+/month.
Executive Perspective. Hands-On Technical Depth.
Most companies do not struggle because they lack AI ideas. They struggle because it is hard to decide which ideas are worth pursuing, what systems need to exist around them, and how the work will fit into real operations.
My perspective is different because I've led AI and data organizations at the executive level and also directly designed and built the systems — production data platforms monitoring 100+ feeds, catalog and enrichment systems operating across 192K SKUs, forecasting and pricing engines run by 22 active accounts, and agentic and knowledge systems used daily. I also built a data science consultancy from zero to $1M+ in annual revenue.
- Strategy grounded in implementation: I help identify what should be built, what should not, and what needs to be true for the work to succeed.
- Complete-system thinking: useful AI is more than an LLM call. It requires software, data, architecture, evaluation, workflows, monitoring, and human judgment — the same thinking behind Collaborative AI.
- Boardroom-to-code depth: I can work with executives on priorities and investment decisions, then work with technical teams on architecture and implementation. More on my background is on the About page.
Executive Advisory & AI Briefings
I also work with executive teams and boards on high-stakes AI decisions: architecture and proposal reviews, build-vs-buy calls, strategy reviews, governance, investment priorities, and organizational direction — including executive briefings and board sessions.
Scoped based on the engagement.
Have a Different AI Challenge?
If your situation does not fit neatly into one of these offerings, reach out anyway. I occasionally take on focused projects around AI strategy, product direction, agentic systems, data strategy, and executive decision support.