Integration design
Define the workflow, data sources, APIs and the actions AI is allowed to take.
AI Integration
AI integration connects an AI capability, such as a language model or Microsoft 365 Copilot, to the business systems and information your processes already use. Umbrella Tech designs and builds these connections for Australian organisations, with deliberate access boundaries, logging and human review where it matters. The result is AI that works inside real workflows instead of beside them, and that your team can operate and support.
The problem
The challenge we help you address
A standalone AI assistant cannot reach the right records or hand work back to the systems people use, so staff copy and paste between windows. Uncontrolled connections create the opposite problem: AI that can see or change more than it should.
The outcome
What the engagement should deliver
The outcome is an integration with a defined role in the workflow, clear ownership and documentation your team can maintain. Human review and escalation are built in where an incorrect output or action would matter. Integration is one part of our AI & Automation work, alongside readiness, agents and training.
How we can help
Engineering
Build authentication, error handling and logging, using APIs, Power Automate connectors or Model Context Protocol (MCP) servers as the design requires.
Microsoft 365 and business systems
Connect AI to SharePoint, Teams, Microsoft Graph and the applications your teams depend on.
Evaluation
Test output quality, access boundaries, failure behaviour and handover to users.
Security and governance considerations
Every integration is a new path to your data. We use dedicated identities with the least access needed, registered in Microsoft Entra ID where possible, keep secrets out of code and log what the AI requested and did. Controls follow your Cybersecurity baseline, and data handling is checked against your Governance & Compliance obligations.
Frequently asked questions
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What is AI integration?
It is the work of connecting AI to your systems so it can use current business information and pass results back into the workflow. Work to integrate AI into business processes usually involves APIs, identity, permissions and testing, rather than a single product.
When should a business use AI integration?
When a useful AI capability is held back because it cannot see the right data or act in the right system, or when staff re-key AI output into other applications. Feasibility depends on available APIs, data permissions and platform limits, which we check first.
What does implementation include?
Design of the workflow and access model, build and configuration, testing with realistic scenarios, and handover with documentation and support arrangements. Larger integrations often start with a proof of concept to confirm value before full build.
How long does an AI integration project take?
It depends on the number of systems, the quality of their APIs, the controls required and how quickly test data and access can be arranged. We confirm scope and timing during discovery.
What are the main security or governance considerations?
Which identity the integration uses, what data it can read, what actions it can take and how those actions are logged and approved. Personal and confidential information also needs a clear handling decision before it is sent to any AI service.
Plan your first integration
Tell us which systems your people work in and where AI could save them handling, and we will help define a practical first integration.