Scalable Enterprise AI Use-Case Implementation

Many companies struggle to scale AI projects into production, resulting in countless failed PoCs. This is often due to immaturity in one or more of the three layers of a complete AI strategy.

Our implementation process draws on experience and lessons learned from countless customer projects. It addresses all layers of the AI strategy, increases your AI maturity and considerably reduces project risk. With a structured set of workshops, assessments, and iterative development based around 4 quality gates; positive business value and business alignment, existence of a usable data basis, existence of an AI operating model, and functional verification via prototypic implementation, we ensure that well-substantiated AI use-case candidates scale properly in an enterprise production environment.

With this offer, we will evaluate and implement one of your potential AI use-cases adhering to industry best practices for the development and operation of AI workloads for enterprise customers.

This offer is composed of the following deliverables:

1. AI Use-Case Envisioning Workshop: An interactive workshop to ensure that the proposed use-case is aligned with the company strategy and will generate business value following implementation:
   Goal: Verify business value generation using AI in this use-case.
   Target audience: Process owner & business departments.
   Effort: 1 or 2-day workshop / use-case
   
   
2. Data Readiness for AI Assessment: This step includes an assessment to ensure that a data basis for the proposed AI use-case actually exists. We will assess aspects such as relevance of the data to the use-case, data quality, data security, and data usability.
   Goal: Verify that data required for the use-case has an appropriate quality, format, & infrastructure
   Target audience: Data Engineer, Data Steward, Process Owner
   Effort: Typically, 2 – 5 days depending on complexity and number of data sources
   
   
3. AI Platform, AI Operating Model & Architecture Check: An assessment to ensure that the customer has sufficient maturity on the Azure platform to host an AI use-case, ensures that the customer has the basic attributes of an AI operating model and that the proposed architecture to the use-case is secure and scalable.
   Goal: Verify that AI platform and app. architecture can scale to the performance requirements
   Target audience: DevOps Engineer, Software Architect, Network Engineer, Network Security
   Effort: Typically, 3 – 5 days depending on complexity of the application and environment
   
   
4. Prototypic Implementation & Verification of an AI Use-Case: This is a prototypic implementation of the defined AI use-case and is tested to ensure technical and business functionality in addition to the verification that the use-case will actually generate true business value for the customer.
   Goal: Create a prototypic implementation of the use-case to verify function and business value
   Target audience: Software Engineer, Software Architect, DevOps Engineer, Process Owner
   Effort: Typically, 10 – 30 days depending on complexity of the application and environment