Service · Implementation
AI Automation Enablement
Safe deployment of enterprise AI tooling and custom automation. Admin configuration, DLP integration, audit logging, and internal agent build out, all with control hooks specified up front.
The gap we close
Adoption is easy. Safe adoption is not.
Most organisations now have access to enterprise AI tooling. Few have configured it for their actual risk profile. Default admin settings retain too much, log too little, share too widely, and leave DLP disconnected.
We deploy AI tooling with the controls already in place. The same practitioner who would assess your governance posture configures the systems being assessed. The result is enablement that does not produce its own findings register six months later.
What we deploy
Tooling we configure to enterprise control standards.
Microsoft 365 Copilot
Tenant-level rollout, sensitivity label integration, Purview DLP scoping, audit log export to SIEM, restricted SharePoint indexing, retention configuration.
ChatGPT Enterprise / Team
Workspace setup, SSO/SCIM provisioning, retention policy, audit export, custom GPT governance, data residency confirmation, member role design.
Claude Enterprise / Team
Workspace configuration, SSO setup, project-level access controls, audit log integration, content filter calibration, role assignment.
GitHub Copilot Enterprise
Organisation-level policy, repository scope rules, public code filter, audit logs, content exclusion configuration, Copilot Workspace governance.
Google Workspace Gemini
Admin console hardening, data region controls, retention configuration, audit log surface, Vault integration where applicable.
Custom agents and workflows
Internal agent build out using Claude, OpenAI, or open-weight models. Includes prompt safety, output filtering, audit trail, and human-in-the-loop checkpoints.
Method
Controls first. Adoption second.
Every enablement engagement defines the control objectives before the tool is enabled at scale. We do not enable, then assess. We assess, then enable.
01
Use case definition
Defined business outcomes per tool. We do not deploy AI for AI's sake.
02
Control objectives
Per use case: data classification posture, retention, audit, identity, monitoring, exit conditions.
03
Configuration
Tenant or workspace configured to control objectives. SSO, SCIM, DLP, retention, audit export.
04
Pilot
Bounded user group, monitored adoption, control evidence captured.
05
Rollout and handover
Phased rollout with documented runbooks. Operational ownership transferred to internal teams.
Engagement
Investment and timeline.
Tooling configuration
From AUD 8,000
Per tool. Includes admin hardening, DLP wiring, audit log export, runbook documentation.
Custom agent build
From AUD 15,000
Scoped per agent. Production-ready with control hooks, audit trail, evaluation harness.
Combined enablement
Quoted
Multi-tool rollout with policy, training collateral, and pilot management. Typical engagements AUD 30,000 to 75,000.
Get started
Deploy AI safely. Once.
A discovery call clarifies your tooling, your control posture, and the realistic shape of an enablement engagement.