Pragmatic AI Advisory
AI Where It Matters.
Simplicity Everywhere Else.
Most consultants will sell you AI for everything. I'll tell you where it actually helps, and where simpler solutions work better, cost less, and ship faster.
"Cameron was exceptionally effective at helping us scope AI correctly - where it adds real value and where rules-based structure is the better solution. His guidance reduced build risk, clarified MVP priorities, and helped our team move faster with more confidence. He's sharp, pragmatic, and focused on shipping cleanly rather than over-engineering."
Eric Kaplan
CEO, Foundry
The AI Hype Problem
Everyone's telling you that you need AI. Chatbots, agents, copilots, RAG pipelines, voice assistants. The pressure to "add AI" is everywhere.
But here's what nobody wants to admit: most AI implementations fail or underdeliver. Not because the technology doesn't work, but because it was the wrong solution for the problem.
A well-designed form beats a chatbot for structured data. A rules-based workflow beats an LLM when the logic is deterministic. A search index beats RAG when your answers are straightforward.
The question isn't "can we add AI?" It's "should we?"
Knowing When to Use AI (And When Not To)
The most valuable advice is often "don't build that with AI."
Where AI Shines
- Unstructured data (docs, emails, images etc.)
- Complex pattern recognition humans can't scale
- Natural language understanding with ambiguity
- Personalization across thousands of variations
- Tasks that would require hundreds of if/else rules
Where Simpler Works Better
- Structured inputs (use forms, not chatbots)
- Deterministic logic (use rules, not models)
- Exact-match lookups (use search, not RAG)
- Sequential workflows (use state machines)
- Clear yes/no decisions (use conditionals)
How I Help
Three ways to work together, depending on what you need.
AI Assessment
Figure out if AI makes sense before you commit. Get clarity on what to build, what not to build, and why.
- Use case evaluation
- Build vs. buy analysis
- Technical feasibility
- Honest recommendation
Sometimes the answer is "you don't need AI."
Implementation Oversight
Your team builds, I guide. Expert oversight to keep your AI project on track and avoid expensive mistakes.
- Architecture review
- Technical QA
- Vendor coordination
- Weekly check-ins
Expert eyes without the full-time cost.
Full Build
End-to-end AI implementation. I build it, you use it. Focused on shipping something that actually works.
- Voice AI optimization
- Self-hosted voice systems
- AI scoping/advisory
- Training and handoff
Ship cleanly rather than over-engineer.
When AI Is the Right Answer
For the problems where AI genuinely helps, these are the solutions I build.
Voice AI Optimization
Latency reduction, voicemail detection, conversion rate optimization. Make your existing voice AI actually perform.
Self-Hosted Voice AI
Build your own voice AI infrastructure. No vendor lock-in, full control, production-ready systems.
AI Scoping & Advisory
Figure out where AI makes sense before you build. Architecture, vendor selection, build vs buy decisions.
You Work Directly With Me
I'm Cameron O'Brien. I build AI systems that actually ship. Voice AI, RAG pipelines, AI-enabled applications. Production systems, not demos.
My approach is simple: figure out if AI is the right tool for your problem first. If it is, build it fast and clean. If it isn't, I'll tell you what would work better.
No junior staff. No handoffs. No account managers. Just direct access to the person doing the work.
Not Sure If You Need AI?
That's exactly the right question to ask. Let's figure it out together. 30 minutes. No pitch. Just an honest conversation about whether AI makes sense for what you're trying to do.