Accelerated Innovation

Evaluating & Selecting Your Models

Evaluating and Selecting the Best Model(s) for Your GenAI Solution

Workshop
Are your teams selecting GenAI models based on demos, benchmarks, or vendor defaults instead of a repeatable evaluation framework?

Choosing the right model is one of the highest-leverage decisions in any GenAI solution, yet many teams still rely on demos, benchmarks, or vendor defaults. This workshop introduces a structured, repeatable approach to evaluating models so teams can make defensible, outcome-aligned decisions across projects. 

To win, teams must consistently select models based on clear objectives, constraints, and a repeatable evaluation process—not intuition or hype. 

The Challenge

Teams evaluating GenAI models often encounter the same obstacles: 

  • Undefined evaluation lifecycle: Jump into testing without a clear sequence from requirements to final selection. 
  • Capability confusion: Struggle to map different model types and strengths to real solution needs. 
  • One-off decisions: Rebuild evaluation logic for every project with no reusable framework. 

These gaps lead to weak model fit, avoidable cost and risk, and inconsistent GenAI outcomes. 

Our Solution

In this hands-on workshop, your team works through a complete model evaluation process and applies it to realistic GenAI scenarios to establish a reusable decision framework. 

  • Outline a clear, end-to-end model evaluation lifecycle. 
  • Examine major model types and the capabilities they are best suited for. 
  • Translate solution objectives into concrete evaluation criteria. 
  • Compare commercial and open-source model options using consistent tradeoffs. 
  • Define a reusable framework teams can apply across GenAI initiatives. 
Area of Focus
  • Outlining the Model Evaluation Lifecycle 
  • Understanding Model Types and Capabilities 
  • Aligning Evaluation to Solution Objectives 
  • Comparing Commercial vs. Open Source Options 
  • Establishing a Reusable Evaluation Framework 
Participants Will
  • Apply a structured lifecycle for evaluating GenAI models. 
  • Match model types to solution needs with greater confidence. 
  • Define evaluation criteria grounded in real business and technical objectives. 
  • Make informed tradeoffs between proprietary and open-source models. 
  • Reuse a consistent framework to select models across projects. 

Who Should Attend:

Technical Product ManagersSolution ArchitectsML EngineersGenAI EngineersEngineering Managers

Solution Essentials

Format

Virtual or in-person

Duration

2 hours 

Skill Level

Introductory to intermediate

Tools

Model evaluation templates and comparison artifacts provided during the workshop

Do your teams have a consistent way to evaluate and select GenAI models?