Working software every 30 days. Not a programme.
The conventional path takes eighteen months, runs $20–50M a year at top-quartile platforms, and asks for faith until the end. Ours ships working software into real hands every thirty days, starting day fourteen — and the IP lands in your tenant, not ours.
We rebuilt the model.
Ship every 30 days.
Working product in the hands of real users on real work, every month. If a sprint slips, scope is cut — never the timeline.
A pod, not an army.
A lean senior team steering a focused engineering pod — with your product owners holding the design pen. The business owns the requirements.
You own the IP.
Every line of code, every prompt, every agent definition lives in your tenant. The team transitions to yours — knowledge transfer is designed in from day one.
Governance, designed in.
Zero data retention on models. Information walls at the data layer. Eval gates and audit logs from day one. Compliance is the foundation, not the retrofit.
Start where you are.
Architecture advisory.
Strategy, target architecture, vendor selection, security posture, business case. Leave-behind: a full phased proposal your board can decide on.
Build it together.
Our senior pod plus your team, knowledge transfer designed in. We staff the lean side; you staff the institutional side. Your people run it from day one.
We run the build.
End-to-end delivery on the 30-day cadence — your product owners steer, your tenant holds everything, your team takes the keys as it scales.
Six sprints to an operating system.
Foundation.
Firmwide AI live by day fourteen. First product running against a live workflow before the month closes.
First products.
First products in daily use across the firm — real users, real work, measured weekly.
Agents draft.
Agents stop answering questions and start drafting work. Time saved per workflow becomes measurable.
Cross-product.
Workflows compose on one memory. Intelligence starts flowing between functions.
Scale.
Eval pass rates gate autonomy. Confidence-gated execution operating at scale.
Operating system.
In daily use across every team. The platform is now how the firm works.
Continuation follows evidence.
Each phase ends with a real go/no-go, decided on pre-agreed metrics — not a rubber stamp.
Are the agents good?
Are agents producing output your senior people accept? Eval pass rates above threshold? Continue or course-correct.
Did Phase 1 deliver?
Hours saved, cycles compressed, products in daily use — measured against the metrics agreed before sprint one. Scale or pause.
Is it in the P&L?
Are the savings auditable where your CFO looks? Is adoption holding without push? Extend or hold.
Is it a moat?
Has the intelligence layer become indispensable? Decide whether to productise it or keep it proprietary.
One day on site. Decision-ready by Friday.
A one-day diagnostic with your executive team: current-state assessment, pain identification, and a working session on where AI earns its keep first. You leave with a gap analysis, a target architecture, and a phased proposal — whether or not you engage us further.