How to Vet Inference Platforms: A Buyer’s Guide for Enterprise AI Teams

In the rapid development of AI products, enterprise teams often overlook inference, leading to increased costs and performance issues as workloads expand. An inference platform can transform this bottleneck into a strategic asset by aligning performance, cost, and control with business objectives, though not all platforms offer the same benefits. The guide highlights the importance of an inference platform, which simplifies running machine learning and GenAI models in production, ensuring product quality and compliance. It also underscores the need for careful evaluation of platforms based on criteria like flexibility, performance optimization, security, and scalability to avoid vendor lock-in and ensure long-term agility. The document reviews leading platforms like Bento, Vertex AI, AWS SageMaker, AWS Bedrock, Baseten, and Modal, comparing their strengths and limitations to help enterprises select the best fit for their specific needs. Ultimately, the guide suggests that the right platform should facilitate rapid deployment, adaptability, and compliance, while mitigating risks associated with vendor dependency.

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