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AI application design
Assess Microsoft Foundry and suitable Azure services against the task and deployment requirements.
Microsoft & Azure practice
Bring AI workflows into the enterprise platforms, identities, and information your organization already relies on.
What we bring together
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Assess Microsoft Foundry and suitable Azure services against the task and deployment requirements.
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Design retrieval and application access around source ownership and the requester’s permissions.
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Connect approved workplace and business-system interfaces, then establish evaluation, release, and support.
Illustrative application
A service team needs an assistant that draws on approved policies and client information, shows the relevant sources, and prepares work for review. The design connects Azure AI capabilities to existing identity and application controls.
AI engineering is connected to data, platform, security, integration, and adoption responsibilities in the same delivery plan.
See how the disciplines fit together ↗Architecture & acceptance
Platform reference: Microsoft Foundry documentation ↗
AI inside your Microsoft environment.
From architecture to operation
A solution architecture, source and identity design, integrated workflow, acceptance evidence, and team handover.
PrismWorks leads the solution architecture, coordinates specialist affiliate contributions, and owns the integrated delivery against agreed acceptance measures.
We confirm the necessary specialists, customer responsibilities, access, milestones, and support in the engagement scope. Your business owner accepts the outcome; your operating team receives the agreed assets and training.
Your next step
Discuss the workflow, the platform environment, and the specialist capabilities your team needs.