Building the Guardrails Before Switching AI On
A major Australian enterprise wanted to introduce an AI coding assistant to help developers work more efficiently, but security, data residency and observability requirements had to be addressed before customer-related data could be involved.
Skillfield established a secure trial environment and aligned security, architecture and governance stakeholders around the controls needed to support safe, compliant adoption, implementing a first-of-its-kind control foundation within the organisation.
The Problem
The organisation wanted to give developers access to an AI coding assistant without compromising enterprise security or compliance. Data residency requirements meant the service had to operate through a regional cloud subscription model rather than international infrastructure.
There was also no established control framework for this category of tool, creating a greenfield security challenge. Responsibility was deliberately split between one team that defined the controls and another that independently verified them. With those functions operating separately, Skillfield orchestrated the cross-team effort to align on requirements, produce the necessary compliance evidence and resolve technical issues before the trial could safely go live.
The Solution
Skillfield led the technical delivery and stakeholder coordination needed to establish the secure, compliance trial environment. This included configuring the regional cloud subscription model to meet data residency obligations and resolving a regional load-balancing issue affecting enterprise-level performance.
Skillfield worked across security architecture and security operations, running live evidence-gathering sessions to demonstrate compliance with an evolving set of controls for which there was no existing precedent.
We also integrated security logging into the organisation’s SIEM platform and secured integration with a responsible AI observability capability that had not previously been prioritised. Working directly with the relevant governance stakeholders, Skillfield built the case for the change and helped move the required controls from concept into operation.
The Outcome
Skillfield’s work established the security, compliance and observability foundations needed to run the AI coding assistant safely within the enterprise. The trial is now live with an initial group of developers, and a broader rollout under evaluation as the organisation builds its case for wider enterprise adoption.
The organisation now has a data-residency-compliant hosting model, an evidenced security control framework where none previously existed, integrated SIEM logging, and observability integration for monitoring responsible AI use.
The additional guardrails implemented can detect and block potentially sensitive information, including payment or personal data, at the point of use. Together, these controls give the organisation a practical foundation for evaluating the assistant in a controlled environment and building the case for a broader enterprise adoption.
