Azure AI Deployment: Co-funded by Microsoft

DataArt’s Azure AI Deployment offering helps organizations move from AI exploration to a deployed pilot workload in production quickly, securely, and cost-effectively. The program combines an AI readiness assessment, Azure landing zone setup, and pilot AI workload deployment to deliver immediate business value while creating a scalable foundation for future AI adoption.

Challenges We Solve:
Many organizations want to adopt AI but face common obstacles:

• Unclear starting point: not knowing how to begin or which use cases bring the most value.
• Data fragmentation: siloed, inconsistent, or incomplete data slowing adoption.
• Pressure for quick results: leadership demands early wins before committing larger budgets./li>
• Governance concerns: compliance, security, and cost control must be in place before scaling.

Our Processes:

I. Assessment & Preparation (2–3 weeks)

• AI Readiness Assessment: reviewing current infrastructure, data pipelines, and governance before deployment.
• Business Use Case Selection: identifying and prioritizing the pilot AI workload for deployment.

II. Deployment (4–6 weeks)

• Azure Landing Zone Setup: deploying a secure, compliant, and scalable Azure foundation.
• Pilot AI Deployment: deploying one chosen workload (such as a chatbot, copilot, document automation, analytics assistant, etc.) on the customer’s Azure subscription as a production-ready deployment designed for long-term use and future scaling.
• Consumption & Cost Modeling: preparing Azure pricing estimates and roadmap for scaling deployments.

III. Post-Deployment (1–2 weeks)

• Deployment Validation: measuring the performance, cost efficiency, and business impact of the deployed workload.
• Future Support for Deployment: providing ongoing support and advisory services from DataArt to operate, enhance, and scale deployments beyond the pilot phase.

Deliverables:

• AI Readiness Report: current state review and recommendations.
• Azure Landing Zone Setup: secure, compliant, and scalable environment.
• Pilot AI Deployment: one prioritized use case chosen by the customer (chatbot, copilot, document automation, analytics assistant, etc.), deployed by DataArt on the customer’s Azure subscription as a production-ready workload designed for long-term use and future scaling.
• Consumption & Cost Estimate: Azure pricing model and roadmap for scaling.
• Enablement & Future Support: ongoing support and advisory services from DataArt to ensure the solution is successfully operated, continuously improved, and scaled into broader adoption.

Key Business Outcomes:

• Fast Path to AI Deployment: moving from “AI interest” to a deployed, working workloads.
• Lower Risk, Lower Cost: Microsoft Azure AI Accelerate funding may cover the significant amount of the engagement cost.
• Secure & Scalable Foundation: governance, compliance, and cost management built in.
• Business-Aligned Outcomes: pilot tailored to the customer’s top priority.
• Future-Proof Deployment: designed for long-term use and easy scaling into additional AI deployments.

The mentioned price is an estimate and may vary depending on factors such as data quality, regulatory requirements infrastructure complexity, etc.

This engagement is eligible for the Microsoft Azure AI Accelerate Funding program. Customers may receive Microsoft co-funding support to partly cover the implementation cost. The final funding decision rests with Microsoft.