LLM EaaS Catalog & Recommendations Best Practices
Enterprises often evaluate models—but struggle to turn results into trusted recommendations. This workshop shows how to validate catalog and recommendation practices in pilots, then scale them into standard workflows and governance.
Leave with a practical pilot-to-scale approach that makes model recommendations credible, repeatable, and ready for enterprise adoption.
Organizations can evaluate models, but still struggle to produce recommendations that are trusted, repeatable, and consistently applied.
- Recommendations lack “real world” proof: Frameworks look good on paper, but haven’t been validated in representative use cases—so adoption is hesitant and inconsistent.
- Pilots don’t translate into standard workflows: Learnings remain local to a team or project, and model selection resets to opinion when new initiatives begin.
- Governance doesn’t capture what was learned: Without institutionalizing results, decision criteria and practices drift—reducing consistency and confidence over time.
If recommendations aren’t proven and operationalized, Model EaaS can’t scale—and model selection stays fragmented.
We help teams validate, refine, and scale model catalog and recommendation practices through a disciplined pilot-to-governance approach.
- Design pilots to test evaluation frameworks and tools: Define pilots that reflect real decision points so teams can prove what works under practical constraints.
- Select representative models and use cases for trials: Choose models and scenarios that mirror enterprise diversity, ensuring learnings translate beyond a single team.
- Collect and analyze results to refine practices: Establish how results will be interpreted and used to improve criteria, thresholds, and recommendation logic.
- Scale successful pilots into enterprise workflows: Convert pilot outputs into standard processes, artifacts, and decision pathways that teams can follow consistently.
- Institutionalize learnings in EaaS governance: Embed validated practices into governance so recommendations remain stable, comparable, and defensible over time.
- Designing pilots to test evaluation frameworks and tools
- Selecting representative models and use cases for trials
- Collecting and analyzing results to refine practices
- Scaling successful pilots into enterprise workflows
- Institutionalizing pilot learnings in EaaS governance
- Define the pilot structure needed to validate model catalog and recommendation practices in real scenarios
- Select representative models and use cases that will produce enterprise-relevant learnings
- Establish how pilot results will be analyzed and translated into refined recommendation practices
- Identify the workflow, artifacts, and roles needed to scale recommendations across teams
- Leave with a plan to embed pilot learnings into EaaS governance for long-term consistency
Who Should Attend:
Solution Essentials
Facilitated workshop (interactive discussion + working session)
4 hours
Advanced
Virtual whiteboard and shared document workspace