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From coordinating teams to configuring quotes, enterprise companies face immense challenges keeping sales operations running smoothly. Fortunately, Configure, Price, Quote (CPQ) software provides specialized solutions purpose-built for streamlining sales in enterprise environments. Customers engage in whichever way they prefer.
However, putting an ML model into production at scale is challenging and requires a set of bestpractices. The solution takes advantage of AWS native features from Amazon SageMaker , building a flexible and extensible framework around this.
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Be backed by enterprise grade security and privacy tooling. Bestpractices to consider: This feature brings significant advantages for hosting your fine-tuned models efficiently. Having a unified developer experience when accessing custom models or base models through Amazon Bedrock’s API.
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