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AI readiness & governance
Use-case workshops, approved tools, policy, data classification, security review and risk register.
Practical. Secure. Controlled.
Use AI to improve the business—without losing control of the data.
Tecoda combines governance, Microsoft, local AI, data integration and software engineering to move AI from experimentation into dependable operations.
Our position
We do not deploy uncontrolled AI agents.
Useful AI needs clear permissions, trusted information, auditability and human ownership. We design the controls before the automation.
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Know what data AI can access
Review permissions, sources, retention and information sensitivity.
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Use the right deployment model
Microsoft cloud, private cloud or offline local models based on risk and use case.
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Keep people accountable
Approvals, exceptions, audit logs and measurable business ownership.
Managed AI services
Four practical ways to start.
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Microsoft Copilot
Licensing, SharePoint and permission cleanup, pilot groups, training and adoption measurement.
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Business agents & automation
Document processing, triage, knowledge assistants, reporting and workflow actions.
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Private & offline AI
Local LLMs, role-based access, document RAG, controlled SQL views and audit logging.
Private AI
Bring intelligence to the data—not the data to an uncontrolled tool.
For sensitive, regulated or disconnected environments, Tecoda can design private AI using local or Australian-hosted infrastructure.
- User login and role-based permissions
- Document ingestion and vector search
- Controlled access to SQL views
- Prompt and response audit trails
- Model and infrastructure lifecycle management
- Human approval for consequential actions
Private AI architecture
Identity → authorised knowledge → model → governed action.
A practical stack for organisations that need useful AI without public data exposure or continuous internet access.
Delivery method
Start small. Prove value. Expand safely.
Discover
Identify high-friction work and assess information risk.
Prepare
Clean permissions, define controls and select the right platform.
Pilot
Build a contained use case with owners and measurable outcomes.
Operate
Monitor usage, improve quality and govern ongoing change.
Find the first AI use case worth doing.
We will prioritise the opportunities by value, complexity, data readiness and risk.