Azure AI Cloud Development. Azure OpenAI built for regulated production. Not for demos.
Azure AI development with Azure OpenAI Service, Azure AI Foundry, Azure AI Search (vector plus hybrid), Document Intelligence, Speech, Vision, and AI Agent Service. BAA-covered for healthcare. SOC 2 Type II and ISO 27001 inherited from Azure. Best for organisations needing enterprise-grade governance, data residency, and compliance on top of GPT-4o, GPT-5, and Claude on Bedrock equivalent capability. Shipped in 6 to 16 weeks. USD pricing.
Tell us your Azure subscription tier, data residency requirements, and the AI use case. Scoped plan plus quote within 3 business days.
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Who we've built for.
How we work
- Overview
- Three phases from Azure tenant audit to live AI in production. We are Microsoft Certified Azure AI Engineers and we ship Azure AI workloads to clients in healthcare, fintech, and regulated industries.
- Step 1 — Scope and architecture
- Two weeks scoping. Azure subscription audit. Data residency requirements (US, EU, UK, Australia, Canada). Azure OpenAI Service region selection. BAA needed (HIPAA workloads). Azure AI Foundry workspace design. Vector store decision (AI Search vs Cosmos DB plus integrated vector vs Postgres pgvector).
- Step 2 — Build in sprints
- 4 to 12 weeks build. Two-week sprints. Eval harness from sprint 1. Prompt versioning via PromptFlow or LangSmith. RAG pipeline with AI Search hybrid retrieval. Document Intelligence for unstructured input. AI Foundry SDK or LangChain orchestration. Cost tracking and quota monitoring.
- Step 3 — Harden and launch
- 1 to 2 weeks hardening plus launch. Pen test and prompt-injection red-team. PII redaction validated. Production deploy with cost guardrails and rate limiting. Hypercare for the first 2 weeks live. Hand-over to your DevOps team with documented runbooks.
Recent cloud and AI infrastructure builds
Recent Azure AI and regulated AI builds.
Azure OpenAI plus Azure AI Search for grounded RAG compliance platform with audit trail, citation enforcement, and BAA-covered Azure infrastructure.
Read case study →
Azure OpenAI plus Document Intelligence plus AI Search for clinical AI workflow with HIPAA architecture, audit-grade logging, and BAA-covered Azure subscription.
Read case study →Azure AI services for care coordination AI with on-device fallback for offline workers and Azure-side RAG for synthesis when connected.
Read case study →What we deliver. Azure AI
Azure OpenAI Service deployment
Azure OpenAI Service with proper region selection for data residency. Model deployments (GPT-4o, GPT-5 when GA, embeddings, DALL-E, Whisper). Provisioned Throughput Units (PTU) for guaranteed capacity vs pay-as-you-go for development. Content filtering policies tuned per use case.
Azure AI Foundry workspace
AI Foundry (formerly Azure AI Studio) workspace for model catalog, prompt flow management, eval pipelines, and deployment. Model fine-tuning via Foundry SDK. Custom prompts versioned in source control. Eval runs tied to CI/CD for prompt regression detection.
Azure AI Search and RAG pipelines
Azure AI Search for hybrid retrieval (vector plus BM25 plus semantic ranker). Integrated vectorisation via Azure OpenAI embeddings. Skillsets for document chunking, OCR via Document Intelligence, entity extraction. Index designed for production with proper scoring profiles.
Document Intelligence and Vision
Azure Document Intelligence for invoice, form, receipt, contract extraction with prebuilt and custom models. Layout API for complex documents. Azure Vision for image classification, object detection, OCR. Custom Vision for client-specific models.
AI Agent Service plus orchestration
Azure AI Agent Service for multi-step agents with tool use, conversation memory, and grounding. Agent orchestration via Semantic Kernel or LangChain. Function calling for tool integration with your APIs. Audit trail of every agent action for compliance.
Governance, cost, and observability
Azure Monitor for AI workload observability. Application Insights for end-to-end tracing. Cost Management for per-deployment budget tracking. Azure Policy for governance (model usage, data residency enforcement, encryption requirements). Microsoft Entra ID for proper RBAC on AI workspaces.
Related capabilities: Cloud DevOps, LangChain development, n8n automation, Workato integration, AI & machine learning, AI chatbot development, Generative AI, Computer vision, Microsoft Power Platform.
Typical engagement ranges
Cloud setup and CI/CD
From $6,000
- Azure AI workspace setup with one production workload, baseline RAG pipeline, eval harness, and DevOps integration.
- Best for first Azure AI workload going to production.
- 6 to 8 weeks.
Platform engineering
From $9,500
- Multi-workload Azure AI platform with shared RAG infrastructure, multi-tenant access patterns, cost guardrails, and observability.
- Common for ISVs building AI products on Azure.
- 8 to 14 weeks.
Enterprise cloud program
From $21,000
- Enterprise Azure AI program with Foundry workspace governance, AI Agent Service rollout, Document Intelligence for back-office, multi-region deployment, and Microsoft Entra ID-driven RBAC across the AI estate.
- 14 to 24 weeks.
DevOps retainer
From $4,500 / mo
- Model monitoring, prompt updates, cost guardrails, Azure infrastructure maintenance, and on-call cover.
FAQ
Azure OpenAI wins for enterprise governance, data residency control (US, EU, UK, Australia, Canada regions), BAA for HIPAA workloads, SOC 2 Type II and ISO 27001 inheritance from Azure, Microsoft Entra ID-driven RBAC, and Provisioned Throughput Units for guaranteed capacity. OpenAI direct wins for fastest access to newest models and lowest per-token cost at small scale. We pick at scoping based on compliance scope and team capability.