Technologies

Microsoft Azure+AI Integration

Azure + AI Integration

Production AI features grounded in your data and Azure governance.

We integrate Azure OpenAI, Cognitive Services, and Azure ML into existing applications — RAG over private data, document intelligence, speech and vision APIs, and agent workflows with content safety, cost controls, and observability built in.

Explore AI Integration on Azure

Why Integrate AI Through Azure

Azure AI keeps models, data, and identity in your tenant — with policies, private networking, and billing you can attribute to products and teams.

Data Residency & Privacy

Private endpoints, managed identity, and no training on your data when using Azure OpenAI enterprise terms.

Composable Services

Mix OpenAI, Speech, Vision, and Document Intelligence behind one integration layer.

Grounded Answers

RAG with Azure AI Search indexes your documents for accurate, citeable responses.

Governance & Safety

Content Safety filters, prompt templates in source control, and per-app rate limits.

AI Integration Reference Architecture

How we connect user-facing apps to Azure AI services with retrieval, orchestration, and guardrails.

Experience

Web / Mobile / Teams
Chat, copilot panels, and workflow assistants embedded in existing products.
API Gateway
APIM or App Service fronts AI routes with auth, quotas, and request logging.

Orchestration

Agent / RAG Service
Python or .NET orchestration with tool calling, memory, and retrieval steps.
Prompt & Config Store
Versioned prompts in App Configuration or Git with environment-specific parameters.

AI Platform

Azure OpenAI
Chat, embeddings, and fine-tuned models with PTU or pay-as-you-go capacity planning.
Cognitive Services
Speech, vision, language, and translator APIs for multimodal features.

Knowledge & ML

Azure AI Search
Vector and hybrid indexes over SharePoint, blobs, and SQL-exported content.
Azure ML
Custom models, batch scoring, and feature stores when off-the-shelf models are not enough.

What We Build with Azure AI Integration

AI capabilities we embed into line-of-business and customer-facing Azure applications.

Copilot & Chat Experiences

Context-aware assistants with citation, feedback loops, and admin analytics.

Document Intelligence

Invoice, form, and contract extraction pipelines into your ERP or workflow tools.

Speech & Translation

Real-time transcription, call summarization, and multilingual support.

Enterprise Search & RAG

Hybrid retrieval with security trimming and refresh schedules for knowledge bases.

Agent Workflows

Multi-step agents that call APIs, databases, and Service Bus with human-in-the-loop approvals.

Azure AI Services We Integrate

Core Azure AI building blocks and how they fit production integration patterns.

Azure Service

Role in stack

Azure OpenAI
LLM chat, embeddings, and assistants with regional deployment and capacity management.
Azure AI Search
Vector and keyword retrieval with semantic ranker for RAG pipelines.
Azure AI Document Intelligence
Structured extraction from PDFs and scans into downstream systems.
Azure AI Content Safety
Filters harmful or off-policy model inputs and outputs at runtime.
Azure Machine Learning
Custom model training, registry, and managed endpoints when domain models are required.
Azure Monitor / App Insights
Token usage, latency, and quality metrics dashboards per AI feature.

How We Deliver AI Integration

Responsible, measurable AI integration — not demo-only chatbots.

1
Use-Case Scoping
Define success metrics, human fallback, and data boundaries before model selection.
2
Evaluation Harnesses
Golden datasets and automated evals for accuracy, latency, and cost per request.
3
Prompt & Model Versioning
Track prompt changes and model deployments like application releases.
4
Least-Privilege Data Access
Index only what each role may retrieve; enforce trimming at query time.
5
Cost & Quota Controls
Per-tenant budgets, caching embeddings, and routing smaller tasks to economical models.