Ideas. Experiments. People. Join the Cybergizer community ↗
Cybergizer /The Cybergizer delivery system

How we build, check
and hand over AI systems.

See how requirements, engineering tools, evaluation and review connect in an AI implementation. We agree the team, environment and acceptance criteria for your scope.

CLIENT CONTEXT

The work
as it is.

  • Users and requirements
  • Code, data and source permissions
  • Business rules and acceptance
→
DELIVERY WORKSPACE

Explore.
Implement.
Check.

  • Approved tools and agent tasks
  • Versioned changes and evaluations
  • Review, traceability and feedback
→
ACCEPTED CHANGE

A result
with an owner.

  • An integrated workflow or feature
  • Release and operating documentation
  • Agreed handover and next measures

A workspace
with boundaries.

Keep engagement-specific code, data and records within the agreed project boundary. Reusable methods and tooling must respect confidentiality, ownership and the terms of the engagement.

Choose development resources around the workload: approved model APIs, appropriate compute and testing tools. Hosting, model use and operational support have different cost and responsibility boundaries.

Execution environment

Make the controls
part of the work.

01

Separate the engagement

Define the project artifacts, identities, permissions and operating environment.

02

Test before release

Use checks matched to expected behavior and representative cases, with a reviewer at the decision point.

03

Track the resource cost

Record relevant model, tool and delivery costs separately from the application’s running costs.

Release is
a decision.

An agent proposal can fail a test or miss a business rule. The responsible engineer investigates the evidence and agrees how to proceed with the client. Tool output alone does not authorize a release.

Try the delivery example ↗