Organizations engage me when an AI or data initiative is too important to hand to a vendor and too ambiguous to staff internally: the architecture is undefined, the prototype is not production-worthy, or the data foundations are blocking everything above them.
Every engagement pairs architecture-level thinking with hands-on implementation from the same person, and ends with a system your team can operate.
A fixed-scope assessment that turns AI ambiguity into a decision-ready roadmap: where AI pays, in what order, and why, before you commit build budget.
ExploreFrom roadmap to production: I architect and personally build the systems the assessment prioritized, including production RAG, agentic workflows, evaluation frameworks, data platforms and the cloud beneath them, with governance and handover built in.
ExplorePrincipal-level AI and data leadership without the full-time hire: architecture review, technical direction between executives and engineering, and embedded hands-on delivery, grounded in years of building inside the Government of Canada.
ExploreThe systems I design and personally build. Each one shows its working architecture, the scope, and the path to production.
Agents that take multi-step operational work off your team end to end, built to the governance bar of enterprise and government environments: every action logged, auditable and reversible.
Answers your people can verify: production RAG that grounds every response in your own documents and cites its sources, the kind of system I have shipped for the United Nations.
Data your AI initiatives and analytics teams can trust: governed pipelines, a modeled warehouse and self-serve BI, built by someone who has shipped this in federal government and telecom environments.
A fixed-scope assessment that turns AI ambiguity into a decision-ready roadmap: where AI pays, in what order, and why, before you commit build budget.
Data and tech leaders, and delivery owners, at large orgs who need to pick the right AI bet, not survey every possibility
Too many AI possibilities, no clarity on value, risk, or sequence
A use-case map scored by value and feasibility, a data readiness check, ROI framing, and a prioritized roadmap you can defend
A defensible decision on your next AI investment, from a consultant who has delivered inside the Government of Canada and can build what the roadmap recommends
From roadmap to production: I architect and personally build the systems the assessment prioritized, including production RAG, agentic workflows, evaluation frameworks, data platforms and the cloud beneath them, with governance and handover built in.
Technology leaders who have a validated roadmap, or a prototype that must become a governed production system, and need senior hands-on delivery rather than a vendor team learning on their budget
The roadmap is clear but capacity, architecture risk, and prototype-to-production gaps block shipping: unreliable retrieval, ungoverned agents, or fragile data foundations
Governed production systems: RAG pipelines with citation and eval, LangGraph and MCP agents with guardrails and audit trails, or cloud-native data platforms shipped with IaC, observability and runbooks, patterns proven in delivery for organizations including the United Nations
A production system your team can operate and extend, with lineage, evaluation and rollback from day one
Principal-level AI and data leadership without the full-time hire: architecture review, technical direction between executives and engineering, and embedded hands-on delivery, grounded in years of building inside the Government of Canada.
CEOs, CTOs and heads of product who need senior AI and data judgment without a full-time hire, to unblock teams, review architecture and keep delivery honest
Teams move fast but without senior technical oversight: architecture drifts, build-vs-buy is guessed, and engineering and executive direction fall out of sync
Fractional leadership: architecture reviews, technical roadmap stewardship, build-vs-buy guidance, team unblocking and hands-on delivery alongside your engineers
Clear technical direction, accountable architecture decisions, and a team that ships with senior oversight without the overhead of a full-time hire
A pragmatic sequence that keeps governance, eval and handover in scope from day one.
Map the problem, data and constraints with stakeholders. Define success, readiness and the shortest path to a production outcome.
Build a working slice over real data: retrieval, tools and prompts, with eval and governance baked in from day one.
Harden for reliability: access controls, observability, latency budgets and fallback paths before autonomous execution.
Ship, monitor and iterate with the team. Handover with runbooks and lineage, not black boxes.
30 minutes to talk through your initiative, the data behind it, and the shortest path to a production outcome.
30 minutes to map the problem, the data and the shortest path to a production outcome. Direct Calendly link. Email fallback available.