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Best practices for building secure applications with Amazon Transcribe

AWS Machine Learning

Amazon Transcribe can be used for transcription of customer care calls, multiparty conference calls, and voicemail messages, as well as subtitle generation for recorded and live videos, to name just a few examples. Applications must have valid credentials to sign API requests to AWS services.

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Drive efficiencies with CI/CD best practices on Amazon Lex

AWS Machine Learning

You liked the overall experience and now want to deploy the bot in your production environment, but aren’t sure about best practices for Amazon Lex. In this post, we review the best practices for developing and deploying Amazon Lex bots, enabling you to streamline the end-to-end bot lifecycle and optimize your operations.

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5 Text Messaging Best Practices for Your SMS Strategy

aircall

With best practices for text messaging, your customer-facing teams will provide better service, while your sales and marketing teams can better interact with leads on a more personalized scale to more efficiently close deals. Why Use Text Messaging Best Practices. SMS Marketing: Text Messaging Marketing Best Practices.

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Build a foundation model (FM) powered customer service bot with agents for Amazon Bedrock

AWS Machine Learning

The structured prompts include a sequence of question-thought-action-observation examples. The action is an API that the model can invoke from an allowed set of APIs. Action groups are mapped to an AWS Lambda function and related API schema to perform API calls. The following diagram depicts the agent structure.

APIs 86
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Detect signatures on documents or images using the signatures feature in Amazon Textract

AWS Machine Learning

In this post, we discuss the benefits of the AnalyzeDocument Signatures feature and how the AnalyzeDocument Signatures API helps detect signatures in documents. Lastly, we share some best practices for using this feature. In the following example, we detect signatures on an employment verification letter.

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Expedite your Genesys Cloud Amazon Lex bot design with the Amazon Lex automated chatbot designer

AWS Machine Learning

Machine learning (ML) technologies continually improve and power the contact center customer experience by providing solutions for capabilities like self-service bots, live call analytics, and post-call analytics. For Event Source Suffix , enter a suffix (for example, genesys-eb-poc-demo ). Save your configuration. Choose Save.

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How Amp on Amazon used data to increase customer engagement, Part 1: Building a data analytics platform

AWS Machine Learning

Amp wanted a scalable data and analytics platform to enable easy access to data and perform machine leaning (ML) experiments for live audio transcription, content moderation, feature engineering, and a personal show recommendation service, and to inspect or measure business KPIs and metrics. Business intelligence (BI) and analytics.