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Streamline RAG applications with intelligent metadata filtering using Amazon Bedrock

AWS Machine Learning

In some use cases, particularly those involving complex user queries or a large number of metadata attributes, manually constructing metadata filters can become challenging and potentially error-prone. The extracted metadata is used to construct an appropriate metadata filter. model in Amazon Bedrock.

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Amazon SageMaker Feature Store now supports cross-account sharing, discovery, and access

AWS Machine Learning

SageMaker Feature Store now makes it effortless to share, discover, and access feature groups across AWS accounts. With this launch, account owners can grant access to select feature groups by other accounts using AWS Resource Access Manager (AWS RAM).

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How Valor Intelligent Processing Uses Speech Analytics to Improve CFPB Compliance and Agent Performance

Provana

For the last few years, collection agencies have been using call center speech analytics to help reduce delinquencies, mitigate losses, and maximize their accounts receivable recovery. Having said that, only malleable speech analytics solutions that quickly evolve as per customer preferences lead to better collection yield.

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Mastering customer health for complex enterprise relationships

Totango

For enterprises, a well-constructed customer health score isnt just a nice-to-have; its a strategic asset that empowers teams to manage complexity, sustain customer satisfaction, and scale their customer success efforts. The enterprise solution Large customer accounts often have layered needs.

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Track LLM model evaluation using Amazon SageMaker managed MLflow and FMEval

AWS Machine Learning

SageMaker is a data, analytics, and AI/ML platform, which we will use in conjunction with FMEval to streamline the evaluation process. Thanks to this construct, you can evaluate any LLM by configuring the model runner according to your model. We specifically focus on SageMaker with MLflow.

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How to Use Shopify for CX: The Complete Guide to Keeping Your Customers Happy

CSM Magazine

Offer Guest Checkout Dont force new customers to create an account to make a purchase. Positive reviews build trust, while constructive criticism helps you improve. Use Customer Data Shopifys analytics tools provide data on shopper behavior, preferences, and purchase history, enabling you to tailor your offerings to match their needs.

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9 Contact Center Quality Assurance Best Practices: Modernize Your Approach, Optimize Your Performance

Calabrio

Automate performance evaluation: AI-driven QA scorecards and analytics streamline the evaluation process, freeing up managers to focus on coaching and development. Frame the process as an opportunity for them to hone their skills, receive constructive feedback, and contribute to the overall success of the team and the company.