Senior technical leadership on demand, for founders who need conviction, not just code. We sit close enough to the metal to catch what a slide deck won't show you.
Every engagement is staffed by the same senior operator who built and owns the ventures below, not a rotating bench of consultants.
Embedded technical ownership: architecture calls, hiring decisions, and the roadmap accountability a non-technical founder can't fake.
Roadmap & architecture ownership
Engineering hiring & team structure
Vendor and tool selection
Board & investor technical narrative
Where AI actually moves the P&L versus where it's a demo. We've shipped it inside our own products, not just advised on it.
Model & vendor selection
Workflow automation design
Build-vs-buy for AI tooling
Cost & latency tradeoffs
Systems designed to survive contact with real usage, and real growth, without a rewrite eighteen months in.
Greenfield system design
Scaling & performance audits
Data model & infra decisions
Security & compliance posture
For investors and acquirers who need an honest read on what's actually been built before the money moves.
Codebase & architecture review
Team & process assessment
Risk & tech-debt scoring
Post-acquisition integration plan
We read the codebase, the team, and the roadmap before we say a word about strategy. Most engagements surface at least one decision that's quietly costing six figures.
A short, direct point of view on architecture, hiring, and sequencing: the kind of document a board can actually act on.
Weekly technical leadership, real-time availability for the calls that can't wait, and direct involvement in hiring and architecture decisions as they happen.
The engagement is done when your internal team can own what we built together, not when the retainer runs out.
Every recommendation we make has already been stress-tested inside a product we own. That's the difference between advice and experience.

Financial-adjacent products can't bolt on compliance after the fact. The technical architecture, audit trails, and data model were designed around regulatory requirements before a line of product UI existed. It's the same discipline we bring to advisory clients handling sensitive data.

Real-time leaderboards, concurrent user load, and a growing user base meant the original architecture had to hold under pressure. This is the same scaling audit and infrastructure judgment we bring to due-diligence and advisory engagements.
Start with a technical audit. Most engagements begin there.
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