End-to-end AI Implementation Services

End-to-end AI implementation services backed by Microsoft certifications and proven delivery frameworks.

Microsoft Solutions Partner with Advanced Specialisation in AI

Proven delivery expertise across government and enterprise organisations in Australia.

Secure, Scalable Enterprise AI for Real Business Outcomes

Powered by Microsoft. From custom AI applications to agentic workflows, we help you deliver secure, scalable AI built for real business impact.

From Experimentation to Production

Most organisations struggle with deploying production-grade AI at scale. Success requires more than model selection: it demands robust architecture, engineering, and governance.

Architecture

Designing scalable AI solutions with appropriate networking, compute resources, model orchestration, data ingestion and integration patterns requires deep expertise.

Security & Compliance

Enterprise AI demands data security, responsible LLM use, AI agent observability, and governance frameworks that balance innovation with risk management.

MLOps Maturity

Moving from notebooks to production requires deployment pipelines, model versioning, automated testing, monitoring, and retraining workflows.

AI Strategy & Enablement Workshop

Unleash Innovation → Explore Technology → Shape Tomorrow

Workshop Outcomes

  • Practical GenAI architecture & security strategy
  • Tailored AI governance framework
  • Intelligent agent demos in real workflows
  • Co-created roadmap for scaling AI enterprise-wide

Topics Covered

  • Solution Architecture: Enterprise-grade AI solution design and integration patterns
  • Security & Privacy: Data security, responsible LLM use, compliance and governance
  • Live Agent Demos: Task-driven AI agents with Azure OpenAI and tool integration
  • Use Case Discovery: Tailored AI opportunities relevant to your business

Agile Agents Enterprise Agentic AI Platform

Production-ready multi-agent platform built on Azure AI Foundry and Azure AI Search. Deploy intelligent agents in weeks, enterprise security, and extensibility through custom development.

Enterprise AI Services

Agentic AI Development

Build autonomous AI agents with Microsoft Agent Framework, LangChain, and Azure AI Agent Service. Pro-code development in Python and C# for complex multi-agent orchestration, tool calling, and enterprise system integration.

  • Microsoft Agent Framework development (Python/C#)
  • Azure AI Agent Service deployment and orchestration
  • Custom function calling and tool integration
  • Retrieval Augmented Generation (RAG) with Azure AI Search
  • Multi-agent coordination and handoff patterns
  • Model Context Protocol (MCP) server integration

Azure OpenAI Service Integration

Deploy GPT-40, GPT-4 Turbo, and 01-preview models in your Azure environment. Custom embeddings, fine-tuning, and prompt engineering with Azure OpenAI SDK for production-grade generative AI applications.

  • Azure OpenAI resource provisioning and configuration
  • Custom model fine-tuning with your proprietary data
  • Embeddings generation with text-embedding-3 models
  • Prompt flow development and optimization
  • Private endpoint deployment and VNet integration
  • Token usage monitoring and cost optimization

Azure Machine Learning & MLOps

Build, train, and deploy custom ML models with Azure Machine Learning. End-to-end MLOps pipelines using Azure DevOps, Python, and ML frameworks (PyTorch, TensorFlow, scikit-learn) for production model lifecycle management.

  • Azure ML workspace setup and compute configuration
  • Custom model development (computer vision, NLP, forecasting)
  • Automated ML (AutoML) for rapid prototyping
  • MLOps CI/CD pipelines with Azure DevOps
  • Model registry, versioning, and lineage tracking
  • Real-time and batch inference endpoints

AI Platform Engineering

Design and deploy scalable AI infrastructure on Azure. GPU compute configuration, Azure Kubernetes Service (AKS) for model serving, Azure Databricks integration, and networking architecture for secure AI workloads.

  • Azure AI Foundry portal setup and project management
  • GPU-enabled compute clusters (NC, ND, NV series)
  • AKS cluster deployment for model inference at scale
  • Azure Databricks integration for large-scale ML
  • Networking architecture (VNet, Private Link, NSGs)
  • Infrastructure-as-code with Terraform and Bicep

AI-Powered Analytics & Fabric

Integrated AI models into Microsoft Fabric and Power BI. Deploy ML models in Fabric notebooks, build AI-powered semantic models, and enable natural language insights with embedded Azure OpenAI capabilities.

  • Fabric data science workspace configuration
  • ML model training and deployment in Fabric notebooks
  • AI Skills integration for intelligent semantic models
  • Power BI Q&A enhancement with Azure OpenAI
  • Real-time scoring with fabric event streams
  • Python/R model execution in Fabric pipelines

AI Strategy, Security & Governance

Establish comprehensive AI governance frameworks, security, architecture, and strategic roadmaps. Workshop-based approach covering GenAI architecture, responsible AI policies, and enterprise-wide capability uplift planning.

  • AI Strategy & Enablement workshops
  • Enterprise-grade AI network and connectivity design
  • Data privacy, encryption, and responsible LLM use
  • Risk management and compliance frameworks
  • AI Centre of Excellence establishment
  • Learn more about AI Strategy & Governance

Low-Code AI Options

For rapid prototyping and citizen developer scenarios, we support Microsoft Copilot Studio for building conversational AI agents and Power Platform AI Builder for no-code model deployment. These complement our pro-code offerings for specific use cases requiring faster time-to-market with limited customization needs.

  • Copilot Studio for conversational agents
  • AI Builder for Power Platform integration

Enterprise AI Implementation Journey

Structured yet flexible delivery approach that accelerates time-to-value while building internal capability through hands-on enablement.

AI Strategy & Architecture Design

1-2 WEEKS
Build autonomous AI agents with Microsoft Agent Framework, LangChain, and Azure AI Agent Service. Pro-code development in Python and C# for complex multi-agent orchestration, tool calling, and enterprise system integration.

  • AI maturity assessment and technical capability analysis
  • Azure architecture design (networking, compute, security)
  • Use case prioritization with effort and ROI estimates
  • Governance, risk management, and responsible AI framework
  • Data privacy strategy and encryption architecture
  • Platform engineering roadmap and team structure

Azure AI Platform Build

2-4 WEEKS
Deploy GPT-40, GPT-4 Turbo, and 01-preview models in your Azure environment. Custom embeddings, fine-tuning, and prompt engineering with Azure OpenAI SDK for production-grade generative AI applications.

  • Azure AI Foundry hub and project provisioning
  • Azure OpenAI Service deployment with private endpoints
  • Azure Machine Learning workspace configuration
  • VNet integration and NSG rule configuration
  • Entra ID integration and RBAC setup
  • Azure DevOps pipelines for MLOps CI/CD
  • Model registry and experiment tracking setup

AI Solution Development

4-8 WEEKS

Build, train, and deploy custom ML models with Azure Machine Learning. End-to-end MLOps pipelines using Azure DevOps, Python, and ML frameworks (PyTorch, TensorFlow, scikit-learn) for production model lifecycle management.

  • Semantic Kernel agent development (Python/C#)
  • RAG implementation with Azure AI Search and embeddings
  • Custom ML model training and evaluation
  • API integration and tool function development
  • Prompt engineering and optimization
  • Unit testing, integration testing, and validation
  • Performance benchmarking and cost optimization

Production Deployment & Enablement

ONGOING
Design and deploy scalable AI infrastructure on Azure. GPU compute configuration, Azure Kubernetes Service (AKS) for model serving, Azure Databricks integration, and networking architecture for secure AI workloads.

  • Practical GenAI architecture & security strategy
  • Tailored AI governance framework
  • Intelligent agent demos in real workflows
  • Co-created roadmap for scaling AI enterprise-wide

Why Agile Insights for Enterprise AI

Microsoft Advanced Specialisation in AI

Advanced Specialisation in AI with certified architects across Azure AI, Azure Machine Learning, and Azure Data platforms. Deep technical expertise in Semantic Kernel, Azure OpenAI Service, and MLOps.

Pro-Code Development Expertise

Seasoned engineers with production experience in Python, C#, and Azure SDK development. Custom agent frameworks, model development, and complex system integration beyond simple configuration.

Production-Ready Accelerators

Agile Agents platform and battle-tested frameworks that reduce AI implementation time by 65%. Reusable patterns for RAG, multi-agent orchestration, and MLOps pipelines.

Enterprise Architecture & Security

Proven experience designing secure AI architectures for government agencies and regulated industries. IRAP assessments, PROTECTED workloads, and complex networking requirements.

End-to-End MLOps Capability

Full lifecycle ML engineering from data preparation through model deployment and monitoring. Azure DevOps integration, automated retraining, and production model governance.

Workshop-Driven Enablement

Hands-on technical workshops with live demos of intelligent agents, architecture deep-dives, and capability uplift planning. We build your team’s skills, not just deliver solutions.

Ready to Build Production AI?

Start with our AI Strategy & Enablement Workshop or schedule a technical deep-dive to explore Azure AI capabilities for your organisation.