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Customer Success Plans Promote Client Satisfaction

Totango

Customer success plans are proposals that document your clients’ goals and how you will help achieve them. A set of key performance indicators and benchmarks to track and measure client progress towards goals. You could then define four minutes and three minutes as benchmarks along your customer’s path to their goal.

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Build a multilingual automatic translation pipeline with Amazon Translate Active Custom Translation

AWS Machine Learning

First, we put the source documents, reference documents, and parallel data training set in an S3 bucket. The source_data folder contains the source documents before the translation; the generated documents after the batch translation are put in the output folder.

APIs 80
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Accelerate Amazon SageMaker inference with C6i Intel-based Amazon EC2 instances

AWS Machine Learning

Refer to the appendix for instance details and benchmark data. To access the code and documentation, refer to the GitHub repo. Given a document as an input, the model will answer simple questions based on the learning and contexts from the input document. The following diagram illustrates the high-level flow.

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How to Bring Agile Innovation to Customer Success

Totango

An agile approach to CS management can be broken down into seven steps: Document your client’s requirements. Document Your Client’s Requirements. Effective agile CS starts with clear, documented requirements based on client engagement and input. Standardize your documentation approach by developing a requirements template.

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Build a secure enterprise application with Generative AI and RAG using Amazon SageMaker JumpStart

AWS Machine Learning

Alternative LLMs can be deployed based on the use case and model performance benchmarks. Embeddings for documents are generated using the text-to-embeddings model and these embeddings are indexed into OpenSearch Service. Prerequisites Before getting started, make sure you have the following prerequisites: An AWS account.

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3 ways to effectively scale your CS operation

Totango

Finally, delivery happens via varied communication mechanisms such as self-service documentation portals, newsletters, and reviews that come together to make a meaningful impact on both sides of the equation. Don’t forget to make your feedback scalable.

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Achieve rapid time-to-value business outcomes with faster ML model training using Amazon SageMaker Canvas

AWS Machine Learning

We estimated these numbers by running benchmark tests on different dataset sizes from 0.5 You can learn more on the SageMaker Canvas product page and the documentation. He helps hi-tech strategic accounts on their AI and ML journey. MB to 100 MB in size. About the Authors Ajjay Govindaram is a Senior Solutions Architect at AWS.