ScaleOperate, improve, expand
Scale turns a successful implementation into a lasting capability. We transfer ownership to your teams, operate selected parts with you where that makes sense, and extend proven patterns across further processes and business areas.
Production is the beginning, not the end.
AI systems need ongoing monitoring, evaluation and improvement as models, data, processes and requirements change. At the same time, what works in the first implementation should become reusable rather than rebuilt for every new process. Scale creates the operating model, tooling and ownership needed for both.
We first define how the system should be operated after go-live: responsibilities, monitoring, evaluations, incident handling, controls and continuous improvement. Depending on your operating model, your teams can take full ownership, Zeyt can provide a managed service for selected capabilities, or we can operate them jointly.
In parallel, we codify what can be reused across future implementations: architecture patterns, agent components, integrations, controls, evaluation methods and delivery practices.
We then apply those foundations to the next processes and business areas, prioritised by business value and readiness rather than expanding by default.
One implementation becomes a lasting capability.
By the end, your teams can operate the system, the reusable parts are codified, and the organisation has a proven model for taking the next processes from redesign into production.
Operating model & ownership
Clear responsibilities, runbooks, controls and tooling for operating the system in production, owned by your teams, jointly operated or managed by Zeyt.
Managed AI operations
Where useful, Zeyt monitors and improves selected AI capabilities, including evaluations, performance, reliability, model changes and operational issues.
Repeatable expansion
Reusable components, architecture and delivery patterns make it easier to take the next process from redesign into production without starting again.
Plan what comes after go-live.
Tell us which AI systems you have in production or close to it. In a 45-minute working session, we look at how they should be operated, what can be reused and which processes could follow.