Scaling AI with MLOps

Unlock new research findings from Informa TechTarget’s Enterprise Strategy Group (ESG)

The pace of AI innovation is unprecedented: Models are morphing, processes and techniques such as RAG and prompt engineering are evolving, and new data sources like vector databases are being introduced. Use cases are proliferating and all require governance to ensure security and safety. Yet with the right enterprise MLOps platform, organizations can efficiently scale while accelerating AI innovation, reducing costs, and minimizing risks.

Read this eBook to learn about the key issues facing their survey respondents:

• 37 percent said scalability is the most significant challenge they face when moving an AI model from development into production.
• 32 percent cited implementation speed is one of the most important attributes they are looking for from their AI infrastructure stack.
• 39 percent indicated flexibility and adaptability were key features organizations want when looking to support AI initiatives.