We ship it into production.
An embedded AI delivery function that sits inside your organisation. We build the placement, wire it into your stack, stand up the evaluation harness, move it past go-live, and graduate the whole thing into your team. Long embed. Senior only. Outcome-weighted.
Implementation firms leave. We graduate.
Every systems integrator in the world can ship an AI pilot. The hard part isn't the ship — it's the year after the ship. Day 90, when eval breaks. Day 180, when drift shows up. Day 270, when someone asks who owns it and no-one has an answer.
The Execution Office is our answer. We embed as your AI delivery function — small, senior, long-tenured — and we stay until the capability lives inside your team. Not a body shop. Not a retainer. A graduation path.
A placement isn't in production until someone on your team can turn it off without calling us.
This is the only engagement we offer where the success metric is our own replaceability. If twelve months in, you still need us to keep the placement alive, we've failed — and we'll tell you so.
A 12-month shape.
Longer engagements add more placements into the line — the shape stays the same.
Build + integrate
Stand up the first placement. Real data, real integration, real users — not a sandbox. Pair-build with your engineers to transfer context as we go.
Eval + harden
Evaluation harness live before production cutover. Guardrails, incident tooling, observability, rollback. The things that make audit sleep at night.
Production + run
Cutover. On-call rotation. Drift monitoring. Quarterly review board. A second placement enters build while the first is in run.
Graduate + exit
Runbook handover. On-call fully in-house. Eval framework your team owns. Dilr.ai shifts to quarterly check-ins — or the next placement.
Small squad. Senior only.
A typical Execution Office squad is three to six people. We don't staff juniors on your engagement and charge partner rates. Every embedded practitioner has shipped AI in production at enterprise scale.
Placement lead
Owns the placement end-to-end. Your single point of accountability. Runs the weekly cadence with your sponsor and the quarterly review with your board.
AI engineer(s)
1–3, depending on scope. Model selection, prompt engineering, eval harness, guardrails, retrieval, fine-tuning. Ships code you can read.
Platform engineer
Integration with your stack. Identity, data pipelines, observability, CI/CD, cost controls. The part everyone forgets until month four.
Eval lead
Owns the evaluation framework — offline, online, adversarial, and customer-facing. Keeps the harness alive past go-live.
Governance partner
Part-time. Bridges the operating model into the live placement. Handles risk, audit, and the difficult conversations with compliance.
Your team
We pair on every piece of the build. By month twelve, your engineers are committing unaided and your product owner runs the placement without us in the room.
A regulated wholesale bank had two years of pilots. We shipped the first one in four months — and the second into the same chassis.
The pilots weren't bad. The chassis didn't exist. Four months to first production cutover, three more to the second placement riding the same eval harness and the same governance boards. By month twelve, the bank's own engineers were committing. Our on-call rotation was fully in-house. We moved to a quarterly check-in.
Composite · details anonymised · representative of engagements