Four engagements
Each service declares what it delivers, how it executes, and where it ends.
None of the four starts with an allocation of hours: each starts with a diagnostic under closed scope.
What changes between them is the object of the decision — cloud foundation, integration layer,
data, or agent containment — and the deliverable that stays with the client team at the end.
Cloud Architecture and Landing Zone
Azure cloud foundation designed for auditability, before the first production workload.
Includes identity, network, policy, data territory, and cost attribution.
Deliverables
Subscription design and governance
Subscription hierarchy, management groups, and resource ownership per workload.
Network and segmentation
Network topology with security perimeter, hybrid connectivity, and egress policy.
Identity and RBAC by design
Least-privilege identity model from day one, including workload identity for services.
Policy and guardrails
Azure Policy and initiatives for automated compliance, no manual procedures.
Method
Every design choice is recorded as an ADR (Architecture Decision Record).
Deliverables include operations runbooks for the most sensitive decisions.
Systems Integration and API Management
Governed integration layer with versioned contracts and end-to-end observability —
so failure shows up before the customer complains. Where there is no migration plan,
we design the platform without downtime.
Deliverables
API catalog and contracts
Every interface with quota policy, versioning, and authentication documented in OpenAPI.
Messaging and resilience patterns
Queues, topics, and retry with idempotency for async flows that cannot lose messages.
End-to-end observability
Distributed tracing across systems with business-impact alerts, not infrastructure metrics.
Zero-downtime migration
Strangler fig pattern for replacing legacy integration without affecting operations.
Method
Load validation before cutover. Every migration starts with a fortnight of mirrored
traffic so differences show up in a report, not an incident.
Before buying a model, verify that the data supports the answer.
We assess lineage, quality, classification, and access — and tell you when the foundation is not ready.
Deliverables
Source inventory and lineage
Which systems provide data, through which path, with which latency. The dependency map before the pipeline.
Quality criteria with owners
Every data domain with quality metrics and a named responsible party — no owner, no governance.
Classification and access control
Sensitive data mapped with access policy per layer (Bronze/Silver/Gold) and access justification.
Readiness report
What would block an AI pilot today — and the shortest path to unblocking it.
Method
The report separates technical blockers from governance blockers.
The first has a timeline; the second needs a decision.
AI Agent Containment and Governance
The pilot becomes production only when the limits are known: scope, authority, audit trail,
emergency brake, and incident response. Without a tested kill switch, it does not reach production.
Deliverables
Agent scope and authority
Definition of what the agent can do, with which tools, and under which conditions. Unplanned action = denied action.
Kill switch and rollback
Tested emergency stop mechanism with documented rollback procedure and target containment time.
Audit trail
Every agent action with identity, timestamp, data read, and decision — readable by auditors and legal teams.
LGPD and applicable regime analysis
Use case analysis against applicable law: legal basis, personal data, data subject rights, and controller liability.
Method
The containment design is tested against failure scenarios before the agent touches production.
The first kill switch is manual; the second is automated.