Build · 3 weeks
Azure AI Foundry Quickstart
Go from zero to production AI in 3 weeks. A deployed AI Foundry workspace with private networking, model deployments, grounding on your enterprise data, and your first AI agent in production.
View quickstart on GitHubWeek 1 — Design
- AI Foundry workspace architecture — projects, connections, compute
- Managed network design — private endpoints, approved outbound
- Model selection and deployment strategy
- Data grounding architecture — Azure AI Search, storage connections
- RBAC and governance model
Week 2 — Build
- AI Foundry workspace deployment via Bicep/Terraform
- Managed network with private endpoints
- Azure OpenAI model deployments
- Azure AI Search index for grounding
- First agent — RAG pattern with enterprise data
Week 3 — Operationalize
- Evaluation framework — groundedness, relevance, coherence
- Content safety configuration
- Monitoring — token usage, latency, error rates
- Cost management — token budgets, model routing
- Knowledge transfer and handover
Deliverables
What you walk away with
Deployed AI Foundry Workspace
Production-ready with private networking and managed compute.
First AI Agent
RAG pattern grounded on your enterprise data — deployed and evaluated.
IaC Codebase
Bicep/Terraform — version-controlled, repeatable, owned by your team.
Evaluation Pipeline
Automated quality metrics — groundedness, relevance, coherence, safety.
Cost Management Dashboard
Token usage tracking, model routing, and budget alerting.
Knowledge Transfer
Recorded sessions on architecture, operations, and agent development.
Ready to deploy AI in production?
Talk to an architect about your AI initiative, data readiness, and deployment strategy.
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