Forward deployed engineering
AI systems fail at the edges: the undocumented exception, the master-data quirk, the approval nobody wrote down. Forward deployed engineers find those by working where the process runs, alongside the people who run it.
What it covers
- 01
Embedded with the business
Engineers sit with process owners and analysts, learn the work as it is actually done, and turn exceptions into requirements.
- 02
Inside your environment
We build in your cloud tenancy and against your systems, under your identity, change-management and security controls, with separate dev, QA and production environments.
- 03
Accountable for production
The engineers who find the problem also ship the system and stay through rollout. Success is measured on the process metric, not on a delivered document.
- 04
Knowledge that stays
Runbooks, architecture records and hands-on enablement, so your teams can operate and extend what we build.
Where this sits
Every engagement follows Strategy, Build, Govern and Operate. This capability does most of its work in the highlighted stage.
- 01 · Strategy
Find where AI pays
We map processes, volumes and systems, then rank use cases by value and feasibility.
A funded roadmap and an AI CoE operating model
- 02 · Build
Embed engineers, ship systems
Forward deployed engineers work inside your teams and connect models to SAP, CRM, identity and data.
Production software in your environment, not a demo
- 03 · Govern
Control every AI action
Identity, policy, approvals, data controls and audit apply before anything executes.
A system your security and audit teams can sign off on
- 04 · Operate
Stay accountable after launch
Monitoring, evaluation, cost management and steady improvement against the original target.
Named owners, runbooks and measured outcomes