95%
of enterprise AI pilots return nothing measurable. The model was rarely the problem. The delivery was.
MIT, 2025
For enterprise
Pilots stall.
We ship to production.
For enterprise teams buried in pilots that never reached production. We embed senior engineers in one workflow, ship a real system in weeks, and hand it over in your cloud. You own everything. Nothing routes back through us.
01The pilot graveyard
You have run this experiment before.
The enterprise AI problem is not a shortage of ambition or budget. It is that the work stops at the demo. The numbers are consistent, and they are about delivery, not models.
3rd
failed pilot is when the executives stop attending the reviews. They call it pilot fatigue. It is a delivery failure, not an AI one.
Deloitte, 2026
$547B
produced no measurable result. The budget is there. The systems in production are not.
Global AI spend, 2025
The deployment gap is a delivery problem. We work exactly where it opens.
02What we are not
Ship, don't advise.
Not a deck
A consultancy hands over analysis and a roadmap, and someone else is meant to build it later. Our only deliverable is a running system with real users on real data.
Not a platform
No product to adopt, no seat licenses, no vendor to renew. We build the system your workflow needs and leave it in your hands.
Not a year
We start with one team and one workflow, and ship to production in weeks. Prove it where the work happens, then decide what comes next.
One team · one workflow · production in weeks
03Security
Ownership is the posture.
The safest vendor is the one that leaves nothing behind.
Most vendor risk exists because the vendor holds your data and runs your system, indefinitely. Our model removes that surface. The system runs in your cloud, on your access controls, and we retain none of it. There is far less to review, because there is far less to trust us with.
How we work with enterprise
Procurement-ready
- T-01You own everything, in your cloudCode, prompts, infrastructure, and evals live in your repositories and your accounts from day one. We retain nothing.
- T-02Least-privilege access, revoked at handoverWe work inside a scoped, auditable access grant, and it ends when the engagement does.
- T-03Your data stays in your accountsNothing needs to leave your cloud, and your data is never used to train models.
- T-04Your IP, from the first commitNo shared repos, no our-keys, no dependency that breaks when we leave.
- T-05We work under your NDA and MSAYour paper, your terms. Certification requirements are scoped into the engagement where they apply.
- T-06We build inside your infrastructureYour cloud, your identity and SSO, your security controls, and the tools you already run. We adapt to your environment instead of forcing our own platform onto it.
- T-07Your team can run and extend itCapability transfer is part of handover. Your engineers can change and grow the system without us, so there is no dependency to renew.
04How to start
One team. One workflow.
You do not have to buy a transformation program to work with us, and you should not. Pick the team with the workflow that hurts most, the one with a real owner and reachable data. We embed there, ship a system to production, and hand it over. The people who scope it build it: senior engineers, not a pyramid where partners sell and juniors deliver. That is the proof. What happens next is your call, made on something running, not a slide.
The first conversation is a 30-minute Workflow Audit. We confirm whether the workflow is a fit, and if it is not, we say so. There is no public pricing because scope is fixed per engagement and quoted after that call.
Forward-deployed engineering began inside large organizations, with a team and a problem. The unit of work has always been a workflow, not an org chart.
05 · Start
Put an engineer
inside your workflow.
Start with our Discovery Agent: a handful of questions, a structured brief, and a Workflow Audit booked straight into the calendar. Prefer to skip the conversation? Book the audit directly.