Two ways to work with us.
Most firms pick a side — they advise, or they build. We do both, because the work is better when advice and execution share a brain.
A — Advisory & Strategy
Senior counsel for consequential AI decisions.
For executives and teams making decisions about where to invest in AI, what to build versus buy, how to govern it, and what to be appropriately skeptical of.
- AI strategy and roadmap development
- Build-vs-buy and vendor evaluation
- Governance, risk, and responsible deployment frameworks
- Executive education and team enablement
- Investment and acquisition due diligence
- Fractional Chief AI Officer engagements
B — Project-Based Engineering
Senior engineering that actually ships.
For teams that need AI engineering to reach production — not just prototype, but deploy systems that work and stay working.
- End-to-end build of AI-powered products and tools
- Production-grade RAG, agents, and LLM systems
- Evaluation, monitoring, and reliability infrastructure
- Modernization of legacy ML systems
- Embedded engineering for time-bound projects
- Hand-off, knowledge transfer, and clean exit
Many clients start with one and move to the other. Some run them in parallel. We scope each engagement to what actually serves the outcome.
What engagement looks like.
We work with companies at very different stages. The substance of the work changes. The standard of it does not.
Track A — Enterprise
If you're an enterprise.
You have data, distribution, and existing systems. You also have constraints — governance, security, integration debt, and stakeholders who need to be aligned before anything ships.
- Translate AI capability into prioritized opportunities tied to P&L
- Architect deployments that satisfy legal, security, and risk
- Embed with internal teams to build, transfer, and exit clean
- Stand up evaluation and monitoring so systems stay trustworthy after launch
Track B — Founder
If you're a founder.
You're moving fast, optimizing for leverage, and need AI to be a real source of advantage rather than a feature checkbox. You don't need a deck. You need an answer and a system.
- Pressure-test the AI thesis underneath your product or business
- Build the core AI system end-to-end, production-ready from day one
- Set up the eval and iteration loop so your team can move quickly after hand-off
- Advise on the harder bets — model selection, agent design, capability boundaries