Data & access
Identify what data will be processed, who needs access, and how retention and permissions should work.
How we work together
Clear scope.
Shared understanding.
Useful AI starts before the model is deployed.
Agree what to run, how it will be used and who manages what.
Built around your institution
Your goals ↘
A deployment brief
Managed AI ↗
One agreed scope. A connected service.
01
Define
Start with the work.
We discuss the people, applications and workflows the deployment needs to support. Your requirements become the basis for model and infrastructure choices.
What we agree
- The intended use and users
- Model capability and evaluation tasks
- Data, hosting and access requirements
- Scope and success criteria
02
Deploy
Build around the brief.
Translate the agreed requirements into an environment: model configuration, compute and the way your team or applications will access the service.
What we review
- Selected models and licensing
- Infrastructure and capacity
- Integration and access approach
- Evaluation before wider use
03
Operate
Keep ownership clear.
Establish how the environment is managed after deployment, how technical issues are handled and how future changes are introduced.
What we define
- Management responsibilities
- Support coverage and escalation
- Model and configuration changes
- Review points as needs evolve
A partnership with clear boundaries
Your work. Our infrastructure.
Agreed responsibilities.
The exact division is set out in the deployment scope. This is the starting point for that conversation.
| Area | Your institution | Zerqilo |
|---|---|---|
| Workload | Define the use case and intended users. | Map the requirements to a deployment scope. |
| Models | Provide evaluation criteria and review outputs. | Support selection, configuration and hosting. |
| Applications & data | Own the applications, data and permissions. | Agree the hosting and access arrangements. |
| Operations | Nominate owners and raise changing needs. | Manage the agreed environment and support scope. |
Details that deserve a conversation
Design the environment.
Define the expectations.
Plan data handling, access and operating requirements alongside your hosting location.
Hosting & capacity
Discuss region requirements, compute needs and availability before making a deployment commitment.
Governance & review
Identify the approvals, documentation and evidence your institution requires before it can proceed.
Common questions
Before we begin.
Do we need to choose a model first?
No. A useful starting point is the work you want the model to perform. Capability, licensing and compute requirements can then guide the selection conversation.
Can we use our existing applications?
Your current applications and preferred access approach form part of scoping. Integration requirements should be reviewed before the deployment is agreed.
Can we begin with a limited scope?
Yes. Discuss a single workflow, team or model first. This creates a practical basis for evaluating the proposed environment and deciding what should come next.
How are costs and service terms agreed?
Compute, usage, hosting and support requirements inform the proposal. Pricing, availability and operating terms need to be confirmed before a deployment commitment.