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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.
The custom Google Chat app, configured for HTTP integration, sends an HTTP request to an API Gateway endpoint. Before processing the request, a Lambda authorizer function associated with the API Gateway authenticates the incoming message. The following figure illustrates the high-level design of the solution.
Note that these APIs use objects as namespaces, alleviating the need for explicit imports. API Gateway supports multiple mechanisms for controlling and managing access to an API. AWS Lambda handles the REST API integration, processing the requests and invoking the appropriate AWS services.
Traditional automation approaches require custom API integrations for each application, creating significant development overhead. In this post, we create a computer use agent demo that provides the critical orchestration layer that transforms computer use from a perception capability into actionable automation.
The Vonage Voice API WebSockets feature recently left Beta status and became generally available. Vonage APIAccount. To complete this tutorial, you will need a Vonage APIaccount. Once you have an account, you can find your API Key and API Secret at the top of the Vonage API Dashboard.
One important aspect of this foundation is to organize their AWS environment following a multi-account strategy. In this post, we show how you can extend that architecture to multiple accounts to support multiple LOBs. In this post, we show how you can extend that architecture to multiple accounts to support multiple LOBs.
Prerequisites Before proceeding, make sure that you have the necessary AWS account permissions and services enabled, along with access to a ServiceNow environment with the required privileges for configuration. AWS Have an AWS account with administrative access. For more information, see Setting up for Amazon Q Business. Choose Next.
In this walkthrough, we are going to create a Ruby on Rails conference call application that utilizes the Nexmo Voice API. To work through this tutorial, you will need a Nexmo account. Set up our Nexmo account, purchase a Nexmo phone number, and create a Nexmo Voice application. Prerequisites. Create a Rails Application.
In this walkthrough, we are going to create a Ruby on Rails conference call application that utilizes the Nexmo Voice API. To work through this tutorial, you will need a Nexmo account. Set up our Nexmo account, purchase a Nexmo phone number, and create a Nexmo Voice application. Prerequisites. Create a Rails Application.
Data privacy and network security With Amazon Bedrock, you are in control of your data, and all your inputs and customizations remain private to your AWS account. Your data remains in the AWS Region where the API call is processed. It is highly recommended that you use a separate AWS account and setup AWS Budget to monitor the costs.
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 APIAccount. To complete this tutorial, you will need a Vonage APIaccount. Prerequisites. and Superuser.
So, in this walkthrough, we are going to recreate the game of telephone utilizing Ruby on Rails, the Nexmo Voice API, and Google Cloud Platform Speech to Text and Translate APIs. Nexmo Account. Google Cloud Platform Account. Setting Up a Nexmo Account. Setting Up a Google Cloud Platform Account.
So, in this walkthrough, we are going to recreate the game of telephone utilizing Ruby on Rails, the Nexmo Voice API, and Google Cloud Platform Speech to Text and Translate APIs. Nexmo Account. Google Cloud Platform Account. Setting Up a Nexmo Account. Setting Up a Google Cloud Platform Account.
Solution overview The architecture at Deutsche Bahn consists of a central platform account managed by a platform team responsible for managing infrastructure and operations for SageMaker Studio. The AI team does not have AWS Management Console access to the AI platform team’s account.
These delays can lead to missed security errors or compliance violations, especially in complex, multi-account environments. Amazon Bedrock Agents is a fully managed service that helps developers create AI agents that can break down complex tasks into steps and execute them using FMs and APIs to accomplish specific business objectives.
Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon through a unified API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.
Add team members using their email addresses—they will receive instructions to set up their accounts. Programmatic setup Alternatively, you can create your labeling job programmatically using the CreateLabelingJob API. On the SageMaker console, choose Labeling workforces.
Today, we are excited to unveil three generative AI demos, licensed under MIT-0 license : Amazon Kendra with foundational LLM – Utilizes the deep search capabilities of Amazon Kendra combined with the expansive knowledge of LLMs. Having the right setup in place is the first step towards a seamless deployment of the demos. Python 3.6
As attendees circulate through the GAIZ, subject matter experts and Generative AI Innovation Center strategists will be on-hand to share insights, answer questions, present customer stories from an extensive catalog of reference demos, and provide personalized guidance for moving generative AI applications into production.
This solution uses an Amazon Cognito user pool as an OAuth-compatible identity provider (IdP), which is required in order to exchange a token with AWS IAM Identity Center and later on interact with the Amazon Q Business APIs. Amazon Q uses the chat_sync API to carry out the conversation. A VPC where you will deploy the solution.
Check out the following demo—seeing is believing! In the demo, our Amazon Q business expert application is populated with some Wikipedia pages. In this post, we walk you through the process to deploy Amazon Q business expert in your AWS account and add it to Microsoft Teams. For Who can use this application or access this API?
In this demo you will be building an extremely simple, yet powerful, real-time transcription service in ASP.NET using Nexmo’s.NET SDK and Microsoft Azure’s Speech SDK. A Nexmo account Sign up here. An Azure Account. Building speech to text transcription services has never been easier. Prerequisites. or higher.
Challenges with traditional onboarding The traditional onboarding process for banks faces challenges in the current digital landscape because many institutions don’t have fully automated account-opening systems. This constraint impacts the flexibility for customers to initiate account opening at their preferred time.
Solution overview When starting with a new use case, you can evaluate how Textract Queries performs on your documents by navigating to the Textract console and using the Analyze Document Demo or Bulk Document Uploader. Adapters can be created via the console or programmatically via the API. What is the account#?
AWS Prototyping successfully delivered a scalable prototype, which solved CBRE’s business problem with a high accuracy rate (over 95%) and supported reuse of embeddings for similar NLQs, and an API gateway for integration into CBRE’s dashboards. The following diagram illustrates the web interface and API management layer.
Share This Story During their annual F8 Refresh conference, Facebook announced the Messenger API for Instagram has exited beta and is now available to all businesses looking to forge deeper relationships with their customers through scalable, 1:1 conversations. The API is open to all businesses. Request a demo. Common Uses.
You can build your own IVR using Ruby on Rails and the Nexmo Voice API. You will need the following to follow along in this tutorial: A Nexmo account. You can do so on your command line with the following: $ rails new nexmo-rails-ivr-demo --skip-activerecord. Ruby on Rails. Getting Started. Create a Rails Application.
You can build your own IVR using Ruby on Rails and the Nexmo Voice API. You will need the following to follow along in this tutorial: A Nexmo account. You can do so on your command line with the following: $ rails new nexmo-rails-ivr-demo --skip-activerecord. Ruby on Rails. Getting Started. Create a Rails Application.
They enable applications requiring very low latency or local data processing using familiar APIs and tool sets. Prerequisites To run this demo, complete the following prerequisites: Create an AWS account , if you dont already have one. Enable the Local Zones in Los Angeles and Honolulu in the parent Region US West (Oregon).
Check out the following demo to see how it works. It’s straightforward to deploy in your AWS account. Prerequisites You need to have an AWS account and an AWS Identity and Access Management (IAM) role and user with permissions to create and manage the necessary resources and components for this application.
The workflow invokes the Amazon Bedrock CreateModelCustomizationJob API synchronously to fine tune the base model with the training data from the S3 bucket and the passed-in hyperparameters. Prerequisites Create an AWS account if you do not already have one. A notification email is sent with the outcome. to create the container image.
You can create your own voicemail application powered by the Nexmo Voice API and Ruby on Rails. A Nexmo Account. Set Up a Nexmo account. From your command line execute the following: $ rails new nexmo-rails-voicemail-demo --database=postgresql. We are now ready to move on to the next step and set up our Nexmo account.
You can create your own voicemail application powered by the Nexmo Voice API and Ruby on Rails. A Nexmo Account. Set Up a Nexmo account. From your command line execute the following: $ rails new nexmo-rails-voicemail-demo --database=postgresql. We are now ready to move on to the next step and set up our Nexmo account.
Model data is stored on Amazon Simple Storage Service (Amazon S3) in the JumpStart account. The web application interacts with the models via Amazon API Gateway and AWS Lambda functions as shown in the following diagram. Prerequisites You must have the following prerequisites: An AWS account The AWS CLI v2 Python 3.6
Amazon API Gateway. The Uneeq digital human interfaces with a simple REST API, configured with Lambda proxy integration that in turn interacts with a deployed Amazon Lex bot. Deploy the integration, which is a simple API Gateway REST API and Lambda function using AWS Serverless Application Model (AWS SAM). AWS Lambda.
Amazon Bedrock is a fully managed service that makes foundational models (FMs) from leading artificial intelligence (AI) companies and Amazon available through an API, so you can choose from a wide range of FMs to find the model that’s best suited for your use case. Model providers can’t access customer data in the deployment account.
Lambda receives the iterative transcripts from EventBridge, determines when a conversation is complete, and invokes the Transcript API within Genesys Cloud and drops the full transcript in an S3 bucket. For more information on setting up your account, refer to the Genesys documentation. Save your configuration. Choose Save.
In this post, we show how native integrations between Salesforce and Amazon Web Services (AWS) enable you to Bring Your Own Large Language Models (BYO LLMs) from your AWS account to power generative artificial intelligence (AI) applications in Salesforce. For this post, we use the Anthropic Claude 3 Sonnet model.
Built on AWS technologies like AWS Lambda , Amazon API Gateway , and Amazon DynamoDB , this tool automates the creation of customizable templates and supports both text and image inputs. This sends the API request to Amazon Bedrock, which is hosting the Anthropic’s Claude 3 Sonnet language model.
In this post, we explain the common practice of live stream visual moderation with a solution that uses the Amazon Rekognition Image API to moderate live streams. You can deploy this solution to your AWS account using the AWS Cloud Development Kit (AWS CDK) package available in our GitHub repo.
At the forefront of this evolution sits Amazon Bedrock , a fully managed service that makes high-performing foundation models (FMs) from Amazon and other leading AI companies available through an API. The following demo recording highlights Agents and Knowledge Bases for Amazon Bedrock functionality and technical implementation details.
Amazon Rekognition includes a simple, easy-to-use API that can quickly analyze any image or video file that’s stored in Amazon Simple Storage Service (Amazon S3). The following table shows the moderation labels, content type, and confidence scores returned in the API response. Graphic Violence L2 92.6% Explosions and Blasts L3 92.6%
In this tutorial, we are going to walk through creating a Ruby on Rails application to forward voice calls via a voice proxy using the Nexmo Voice API. To work through this tutorial, you will need a Nexmo account. Sign up now if you don’t already have an account. Prerequisites.
In this tutorial, we are going to walk through creating a Ruby on Rails application to forward voice calls via a voice proxy using the Nexmo Voice API. To work through this tutorial, you will need a Nexmo account. Sign up now if you don’t already have an account. Prerequisites.
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