“We needed a partner who understood both the technical depth of Azure OpenAI and the governance requirements of an enterprise.”
Enterprise Program Brief
Azure AI Foundry for Enterprise AI Applications
This program gives technical teams Azure AI Foundry experience for building production-ready AI applications. Participants work through model selection, prompt flow design, evaluation pipelines, and governance controls needed for enterprise rollouts.
VNode ITeSIntermediateIn Demand
Download Program Brief (PDF)Program Snapshot
Engagement scoped to cohort
Duration2-3 Days
FormatVirtual / Onsite
LevelIntermediate
- MCT-led delivery
- Private cohort / virtual ILT
- Typical response: 1 business day
Scoping call typically scheduled within one business day
VNode ITeS delivers Azure AI Foundry for Enterprise AI Applications as an MCT-led VNode ITeS program for AI Engineers, Solution Architects, and Technical Leads. Typical duration is 2-3 Days (Virtual / Onsite). Labs follow production-shaped scenarios rather than slide-only walkthroughs. Private cohorts can shift emphasis by role mix, workspace or repo constraints, and rollout timing.
Audience Profile
Built for these roles
AI Engineers, Solution Architects, and Technical Leads
- Tailored Team Delivery
- Implementation-Focused
Overview
Executive overview
Build and operationalize enterprise AI applications using Azure AI Foundry, including model evaluation, prompt workflows, and deployment guardrails.
Prerequisites
- Working knowledge of cloud and API fundamentals
- Basic understanding of LLM concepts and prompt design
- Familiarity with Azure fundamentals is recommended
Program Outcomes
Capabilities your teams will gain
- Use Azure AI Foundry to evaluate and select fit-for-purpose models
- Design prompt flows and orchestrations for real business use cases
- Apply safety, content filtering, and evaluation practices before release
- Plan production deployment patterns with governance and observability
Enterprise Delivery
Private cohort delivery
VNode-designed, vendor-aligned instructor-led program. Scope role mix, delivery format, and rollout goals for your cohort.
Curriculum
Curriculum roadmap
- Azure AI Foundry Studio navigation and project setup
- Model catalog evaluation and selection methodology
- Prompt Flow design and orchestration
- Evaluation, content safety, and responsible AI governance
1Module 1
Azure AI Foundry Studio
+
Module 1
Azure AI Foundry Studio
Navigate and configure AI Foundry projects, connections, and compute resources for enterprise AI application development workflows.
- configure AI Foundry projects
- and compute resources for enterprise AI application development workflows
2Module 2
Model Catalog and Selection
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Module 2
Model Catalog and Selection
Evaluate and deploy models from the AI Foundry catalog using structured comparison criteria for capability, cost, and compliance.
- deploy models from the AI Foundry catalog using structured comparison criteria for capability
- and compliance
3Module 3
Prompt Flow Design and Orchestration
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Module 3
Prompt Flow Design and Orchestration
Build and test prompt flows that orchestrate AI tasks, retrieval steps, and output processing for production AI applications.
- test prompt flows that orchestrate AI tasks
- retrieval steps
- and output processing for production AI applications
4Module 4
Evaluation, Content Safety, and Governance
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Module 4
Evaluation, Content Safety, and Governance
Implement evaluation pipelines, content filtering, responsible AI checks, and observability patterns for governed AI deployment.
- Implement evaluation pipelines
- content filtering
- responsible AI checks
- and observability patterns for governed AI deployment
Delivery Models
Delivery models
Virtual ILTOnsiteHybridExecutive WorkshopBootcampWeekend
Engagement Fit
Engagement fit
- Implementation-focused labs
- Private cohort delivery
- Intermediate practitioner depth
- Business outcome alignment
Enterprise Customization
Enterprise customization
Tailor this program to your organization's priorities: Helps enterprise teams move from AI experimentation to production using a governed model catalog, orchestration tools, and repeatable delivery patterns.
- Use-case-specific labs aligned to your industry
- Model benchmarking track based on cost/latency/quality targets
- Governance and rollout blueprint tailored to enterprise controls
Resources
Program resources
Yes. Most enterprise clients prefer private delivery scoped to role mix, timezone, and rollout timeline. We align lab environments and scenarios to your tenant context where applicable.
Enterprise Proof
Trusted delivery outcomes
Retail & E-commerce
Representative Retail Analytics Team
Instead of treating reporting as a tooling issue alone, the work focused on consistency, governance, and shared delivery practices across analysts and engineering teams.
- Higher consistency in report design practices
- Improved collaboration between analysts and engineering teams
Healthcare
Representative Healthcare Product Team
The engagement helped product and engineering stakeholders move from interest in AI to clearer implementation choices, security expectations, and prototyping discipline.
- Stronger alignment between product and engineering teams
- Improved clarity on prototype-to-production requirements
Delivery Capability
Enterprise-grade instruction
MCT-led delivery
Programs led by Microsoft Certified Trainer practitioners
Enterprise program oversight
Founder-led specialist delivery with structured rollout planning
Global delivery
APAC · EMEA · Americas · Virtual & Onsite
Implementation-focused
Hands-on labs aligned to production scenarios
