NTT DATA - GenAI Landing Zone

The NTT DATA Managed AI Landing Zone is a professional services offering that enables organizations to rapidly design, deploy, and operationalize secure, scalable, and governed Generative AI and Agentic AI solutions on Microsoft Azure. The service helps customers move beyond isolated proof-of-concepts by establishing a production-ready AI platform built on Microsoft Azure best practices, reducing implementation risk while accelerating time-to-value.

Our professional services support customers in getting started with Microsoft Azure AI services or extending existing Azure environments by providing the architecture, implementation expertise, governance frameworks, and operational capabilities required to deploy enterprise-grade AI workloads. Whether customers are beginning their AI journey or scaling existing solutions, NTT DATA delivers the technical know-how, reusable accelerators, and industry experience needed to build a secure and future-ready AI platform.

The engagement establishes an Azure-native AI foundation with integrated networking, identity, security, DevSecOps, governance, monitoring, and FinOps capabilities. Customers benefit from a reusable platform that supports Retrieval-Augmented Generation (RAG), AI agents, multi-agent orchestration, enterprise knowledge integration, and modern AI application development.

The solution leverages core Microsoft Azure services including:

• Azure AI Foundry for AI development, model management, evaluation, and agent development
• Azure OpenAI Service for enterprise access to leading foundation models
• Azure AI Agent Service for developing and orchestrating autonomous AI agents
• Microsoft Fabric and OneLake for enterprise knowledge integration, analytics, and AI-ready data access

The engagement also includes Infrastructure-as-Code (IaC), CI/CD pipelines, security policies, landing zone deployment, governance controls, operational handover, and knowledge transfer. NTT DATA's reusable Azure accelerators significantly reduce implementation effort while enabling customers to rapidly onboard new AI use cases, standardize security and compliance, and establish a scalable enterprise AI operating model.

Typical customer outcomes include:

• Accelerated deployment of production-ready AI workloads on Microsoft Azure
• Faster onboarding of AI teams and new business use cases
• Reduced implementation risk through Azure best practices and standardized architecture
• Enterprise-grade security, governance, and compliance aligned with organizational policies
• Improved operational visibility through monitoring, FinOps, and cost transparency
• A reusable Azure AI platform supporting future AI applications, copilots, and autonomous agents
• Reduced time from concept to MVP through proven implementation accelerators and reference architectures

This professional services engagement enables organizations to confidently adopt and expand their use of Microsoft Azure while establishing a secure, governed, and scalable foundation for enterprise Generative AI and Agentic AI innovation.