WHAT TO EXPECT

Knowing whether an AI/ML offering is real or vaporware requires a thorough examination by experts with specialized skills beyond traditional software development. Kickdrum’s experts in data science, pipelines, predictive analytics, and intelligent automation identify key areas of concern and missing best practices to reduce risk and uncertainty by reviewing:

• Strategy and Processes: Kickdrum reviews strategy materials and conducts interviews with executive and technology leaders to understand the state of AI/ML, including personnel commitments and processes. 

• Infrastructure and Architecture: Kickdrum reviews documents and interviews technical resources to understand and define the architecture of the AI/ML practice, including data ingestion processes, model management and promotion, and performance and maintainability of models and supporting infrastructure.

• Identify Risks and Define Potential Business Impact: Kickdrum documents risks to scalability, extensibility, reliability, and resilience, along with the corresponding business impact. We will also offer options for risk remediation tactics and provide prioritized recommendations.

• AI/ML Maturity and Credibility: Kickdrum reviews AI models and data science practices to uncover gaps in capabilities, highlight immature practices, and recommend improvements to team structure, measurements, and methodology.

HOW IT WORKS

Kickdrum’s diagnostic, non-invasive approach to AI Feasibility combines leadership and customer interviews, technology and project roadmaps, industry research, and additional inputs to assess  people, processes, data, architecture, operational burdens, and security and compliance issues. Within a couple weeks, Kickdrum delivers  a full AI feasibility assessment that includes:

• A thorough report detailing infrastructure and architecture, identifying risks and threats to scalability, reliability, and resilience

• Insight into machine learning processes, practices, and capabilities including staffing and procedures

• A full evaluation covering maturity and credibility of AI/ML practices and offerings