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Enhance customer support with Amazon Bedrock Agents by integrating enterprise data APIs

AWS Machine Learning

In this post, we guide you through integrating Amazon Bedrock Agents with enterprise data APIs to create more personalized and effective customer support experiences. An automotive retailer might use inventory management APIs to track stock levels and catalog APIs for vehicle compatibility and specifications.

APIs 127
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Record a Call in Ruby with Vonage Voice API WebSockets

Nexmo

The Vonage Voice API WebSockets feature recently left Beta status and became generally available. Vonage API Account. To complete this tutorial, you will need a Vonage API account. Once you have an account, you can find your API Key and API Secret at the top of the Vonage API Dashboard.

APIs 125
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Integrate dynamic web content in your generative AI application using a web search API and Amazon Bedrock Agents

AWS Machine Learning

Amazon Bedrock agents use LLMs to break down tasks, interact dynamically with users, run actions through API calls, and augment knowledge using Amazon Bedrock Knowledge Bases. In this post, we demonstrate how to use Amazon Bedrock Agents with a web search API to integrate dynamic web content in your generative AI application.

APIs 105
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Audit Phone Calls with Event Sourcing in.NET

Nexmo

Luckily for us, Vonage has a fantastic API for tracking phone calls ! We’ll use the Vonage API and build a.NET Core application that stores and displays this information by using event sourcing. Vonage API Account. To complete this tutorial, you will need a Vonage API account. Prerequisites. and Superuser.

APIs 139
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Track LLM model evaluation using Amazon SageMaker managed MLflow and FMEval

AWS Machine Learning

Using SageMaker with MLflow to track experiments The fully managed MLflow capability on SageMaker is built around three core components: MLflow tracking server This component can be quickly set up through the Amazon SageMaker Studio interface or using the API for more granular configurations.

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The Essential Guide to WFM – Key Features to Look For

CCNG

Forecasting Core Features The Ability to Consume Historical Data Whether it’s from a copy/paste of a spreadsheet or an API connection, your WFM platform must have the ability to consume historical data. Scheduling Core Features Matching Schedules to Forecasted Volume The common definition of WFM is “right people, right place, right time”.

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Build a receipt and invoice processing pipeline with Amazon Textract

AWS Machine Learning

One area that holds significant potential for improvement is accounts payable. On a high level, the accounts payable process includes receiving and scanning invoices, extraction of the relevant data from scanned invoices, validation, approval, and archival. It is available both as a synchronous or asynchronous API.

APIs 121