Implementation planning
Turn loose AI goals into scoped use cases, architecture options, risks, delivery phases, and success criteria.
Enterprise AI implementation, without the theater
Practical AI systems for teams that need working software, not a slide deck.
I help organizations evaluate AI opportunities, design implementation plans, and build the pieces that make those plans real. The work is small-team, hands-on, and grounded in the constraints enterprises actually have.
Who I am
A technical partner for AI work that needs to survive contact with production.
ContextB is my independent consultancy for enterprise AI implementation. Most engagements start with a focused project: a system to design, a workflow to automate, or a technical decision to de-risk. When the work proves useful, it often continues as fractional CTO involvement, giving the organization senior technical leadership without hiring a full-time executive.
I work best with teams that already have real operational pressure: internal workflows that are too manual, support or knowledge processes that need better tooling, or product ideas that need a credible technical path. My role is usually part architect, part engineer, and part translation layer between leadership goals and implementation reality.
I help narrow broad AI ambition into scoped projects, build or guide the systems that prove the value, and stay involved as the technical partner who keeps the work moving as priorities expand.
What I can offer
Focused help where AI strategy has to become software.
Prototype to production
Build thin but serious systems that connect models, internal data, permissions, workflows, and observability.
Technical review
Assess an existing AI plan or build for feasibility, security, maintainability, vendor fit, and operational risk.
Team enablement
Work with engineering and product teams to establish patterns they can keep using after the engagement ends.
How engagements work
Small, concrete, and honest about tradeoffs.
- Discovery is short and oriented around whether there is a useful project.
- Initial engagements are scoped to a specific system or decision and typically run several months.
- Successful projects often extend into ongoing fractional CTO support as the work grows beyond the first implementation.
- Recommendations include implementation costs and operational constraints.
- Demos and prototypes are built with a clear path toward maintainable systems.
- Communication is direct, written down, and easy for your team to reuse.
Have an AI implementation problem worth discussing?
Send a short note about what you are trying to do, where you are stuck, and what kind of help would be useful.
Contact ContextB