Requirements
Map the workloads you plan to run, the risk posture they need, and the controls your regulators expect.
What you walk away with
A governed baseline
Identity, guardrails and policy enforced at the platform level
Standard retrieval and orchestration patterns every use case inherits
Content safety and evaluation gates before each release
A reusable pattern catalog so use case four ships in days
Evidence and control
End-to-end audit traceability of AI actions and decisions
Model and prompt versioning with quality gates
Continuous monitoring of behavior and output quality
Documentation your auditors and regulators can follow
Agentic FinOps
Cost telemetry per agent, per workflow and per outcome
Dashboards your CFO can read without translation
Budget alerts and drift detection before the invoice arrives
A clear view of which workloads earn their keep
How the work phases
Design
Target architecture for identity, retrieval, orchestration, evaluation and cost telemetry on your chosen platform.
Build
Stand up the harness, wire the guardrails, implement evaluation gates and the FinOps layer.
Operate
Hand over the pattern catalog, dashboards and runbooks, then support the first workloads through the gates.
Built for
Organizations scaling past their first one or two AI use cases
A managed cloud tenant and an established platform or data team
Microsoft Foundry, Microsoft Fabric or Databricks estates
Regulated industries where traceability is not optional
Executive sponsorship from the CIO, CTO or CISO
At a glance
Scoped per estate, phased from requirements to production
Microsoft Foundry, Fabric and Databricks
Evaluation gates and content safety before every release
Full audit traceability for your auditors
Agentic FinOps: cost per agent, per workflow, per outcome
Where it leads.
A platform is only worth what runs on it. Most clients pair this with Agent and Application Build to ship the first workloads, then Agent Assurance to keep quality and cost honest as the catalog grows.
Build the harness before you need it.
Retrofitting governance and cost control onto a live AI estate costs more than building them in. We can show you what that looks like for yours.