- strategize.
- design.
- prototype.
- build.
- train.
- ship.
What I do. And how.
AI Strategy & Roadmapping
Most companies know AI matters but don't know where to start. I help figure out where AI will actually move the needle for your business, and map out a realistic plan to get there. No hype, just what's worth building.
2-4 week engagement producing a prioritized AI roadmap with clear milestones and resource requirements.
- AI readiness assessment
- Opportunity identification & prioritization
- Technology selection & architecture recommendations
- Implementation roadmap with milestones
- ROI modeling & business case development
Founders and product leaders who know AI matters but need help figuring out what to actually build first.
LLM Implementation
Building with LLMs requires more than API calls. I handle the full implementation, from architecture and prompt engineering to deployment, so you end up with something that actually works in production, not just a demo.
4-12 week embedded engagement, working directly with your engineering team.
- Architecture design & system planning
- RAG pipeline development
- Prompt engineering & optimization
- Fine-tuning & evaluation frameworks
- Production deployment & monitoring
Engineering teams building LLM-powered features who need architectural guidance and hands-on implementation support.
AI Education & Training
AI tools are only as good as the people using them. I design and deliver training programs tailored to your team's skill level and goals — whether that's helping leaders understand what's possible, or getting teams hands-on with AI design tools and workflows.
Single-day workshops to multi-week training programs, tailored to your team size and objectives.
- Custom curriculum design
- Hands-on workshops & bootcamps
- Executive AI literacy sessions
- AI design tools & workflow training
- Ongoing learning resources & documentation
Organizations that want their teams to actually understand and use AI effectively, not just talk about it.
UX/UI Design for AI Products
AI products fail when users don't trust or understand them. I design interfaces for AI-powered products, including conversational UIs, dashboards, and generation tools, making sure the technology actually serves the people using it.
Flexible engagement model, from design sprints to ongoing product design partnership.
- User research & needs analysis
- Interaction design & prototyping
- Design system development
- Usability testing for AI interfaces
- Trust & transparency design patterns
Product teams building AI-powered products who need interfaces that users actually trust and adopt.
How it works.
Understand
I learn your business, your users, and what you've already tried.
Plan
I figure out what's worth building and how to build it.
Build
I ship early, get feedback, and refine. You see working software, not status updates.
Refine
After launch, I optimize what's working and fix what isn't.
Frequently asked questions.
What does an AI consultant do?
An AI consultant helps businesses identify where artificial intelligence can create measurable value, then designs and builds the systems to deliver it. This includes assessing AI readiness, selecting the right technologies, architecting LLM pipelines, and shipping production-ready AI products. A good AI consultant bridges the gap between business strategy and technical implementation.
How long does an AI implementation typically take?
AI implementation timelines vary based on complexity. An AI strategy and roadmap typically takes 2-4 weeks. LLM implementation projects run 4-12 weeks for production deployment, including architecture design, RAG pipeline development, prompt engineering, and monitoring setup. Simpler integrations like adding AI features to an existing product can ship in as little as 2-3 weeks.
Do I need AI for my business?
Not every business needs AI, but most can benefit from it. AI is worth exploring if you have repetitive processes that could be automated, large volumes of unstructured data, customer-facing workflows that need personalization, or content creation needs at scale. The best approach is an AI readiness assessment that evaluates your specific opportunities and their potential ROI before committing to implementation.
What's the difference between AI strategy and LLM implementation?
AI strategy is the planning phase: identifying which AI opportunities will create the most business value, selecting technologies, and building a roadmap with milestones. LLM implementation is the building phase: architecting systems, developing RAG pipelines, engineering prompts, fine-tuning models, and deploying to production. Strategy answers 'what should we build and why.' Implementation answers 'how do we build it and ship it.'
What industries do you work with?
I work across industries including technology, SaaS, education, real estate, financial services, and professional services. My clients range from early-stage startups building their first AI product to enterprise companies integrating AI into existing workflows. The common thread is organizations that want to move from AI ambition to production reality with a hands-on partner who designs, builds, and ships.
How is your approach different from other AI consultants?
Most AI consultants deliver strategy decks and leave. I design, build, and ship working products. I combine business experience from finance at BMO, product design expertise, and engineering capability, so you get one person who understands the business case, can design the user experience, and can build and deploy the technical solution. You get a working product, not a presentation about one.