Event details
Plan how you'll scale inference in 2027
Models and agents are moving into production, and 2027 budgets will follow. The decisions you make now determine how inference scales, where it runs, and whether cost, latency, and reliability hold steady as demand grows.
Plan, compare, decide
Join Naveen Chhabra, Principal Analyst at Forrester, and Shadi Saba, VP of AI/ML Engineering at CoreWeave, for a year-end look at where inference is headed in 2027. Naveen breaks down the infrastructure trends shaping AI leaders' plans. Shadi shares the trends CoreWeave sees running inference in production. You'll leave with a framework for comparing deployment options and deciding what to commit to now. We'll close with how CoreWeave Forge connects inference to the rest of the AI loop, so production results feed your next model and agent improvement.
In this webinar, we’ll cover:
- Which inference trends are likely to shape infrastructure planning in 2027
- How production inference requirements differ from experimentation, and what that changes for capacity and budget
- How to compare deployment options on cost, latency, reliability, and control
- Which decisions to make now and which to defer
- How CoreWeave Forge connects inference, observability, and training so you can turn production results into compounding improvement
- What to ask vendors and internal teams during 2027 planning
Register to take away a decision framework for your 2027 inference roadmap and start building on CoreWeave Forge.
