AI Launch: 8-Wk Implementation

Target Audience

• Companies seeking to scale AI initiatives: Organizations that have completed multiple Proofs of Concept (POCs) and are ready to move toward their first live AI deployment or pilot.
• Organizations building a robust foundation: Those looking to establish a strong Data & AI foundation to support scalable, secure, and ethical AI applications.

Key Deliverables

• Deployed AI Application: A production-ready AI solution addressing one or more high-value business use cases.
• MVP Data & AI Platform:
  • Built and deployed using Infrastructure-as-Code (IaC) principles
  • Enables scalability, security, and repeatability of AI workloads
• End-to-End AIOps Framework:
  • Continuous integration and delivery pipelines for model development and deployment in Azure
  • Automated monitoring, retraining, and performance tracking
• Responsible AI Artefacts: Governance documentation, fairness and bias assessments, and ethical AI practices.
• Training Materials and Documentation: Comprehensive guides and reference materials for users and technical teams.

Scope of Work and Activities

• Platform Setup: Configure and deploy core components of the Data & AI platform required for secure, scalable, and ethical AI applications.
• Use Case Development: Identify, develop, and deploy one or two high-value AI use cases into production.
• Testing and Validation: Conduct technical validation (performance, reliability, scalability) and business validation (impact, ROI, user feedback).
• Coordination with IT Governance and Operations: Collaborate with internal teams to ensure alignment with enterprise standards, compliance, and production roll-out requirements.
• Pilot Execution and Roll-Out:
  • Deploy the AI applications for real users in a controlled pilot
  • Conduct user training and gather feedback for iterative improvement