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Today, we’re excited to announce multi-turn conversation with an agent node (preview), a powerful new capability in Flows. This new capability enhances the agent node functionality, enabling dynamic, back-and-forth conversations between users and flows, similar to a natural dialogue in a flow execution.
In this post, we show you an innovative solution to a challenge faced by security teams in highly regulated industries: the efficient security analysis of vast amounts of video recordings from Privileged Access Management (PAM) systems. We demonstrate how you can use Anthropic’s Claude 3 family of models and Amazon Bedrock to perform the complex task of analyzing video recordings of server console sessions and perform queries to highlight any potential security anomalies.
Accurately converting free text inputs into structured data is crucial for applications that involve data management and user interaction. In this post, we introduce a real business use case from Cato Networks that significantly improved user experience. By using Amazon Bedrock, we gained access to state-of-the-art generative language models with built-in support for JSON schemas and structured data.
This post introduces HCLTech’s AutoWise Companion, a transformative generative AI solution designed to enhance customers’ vehicle purchasing journey. In this post, we analyze the current industry challenges and guide readers through the AutoWise Companion solution functional flow and architecture design using built-in AWS services and open source tools. Additionally, we discuss the design from security and responsible AI perspectives, demonstrating how you can apply this solution to a wider range of industry scenarios.
The Education and Training Quality Authority (BQA) plays a critical role in improving the quality of education and training services in the Kingdom Bahrain. BQA reviews the performance of all education and training institutions, including schools, universities, and vocational institutes, thereby promoting the professional advancement of the nation’s human capital. In this post, we explore how BQA used the power of Amazon Bedrock, Amazon SageMaker JumpStart, and other AWS services to streamline the overall reporting workflow.
This post shows how MuleSoft introduced a generative AI-powered assistant using Amazon Q Business to enhance their internal Cloud Central dashboard. This individualized portal shows assets owned, costs and usage, and well-architected recommendations to over 100 engineers.
In this post, we propose a solution using DigitalDhan, a generative AI-based solution to automate customer onboarding and digital lending. The proposed solution uses Amazon Bedrock Agents to automate services related to KYC verification, credit and risk assessment, and notification. Financial institutions can use this solution to help automate the customer onboarding, KYC verification, credit decisioning, credit underwriting, and notification processes.
In this post, we explore how Deep Instinct’s generative AI-powered malware analysis tool, DIANNA, uses Amazon Bedrock to revolutionize cybersecurity by providing rapid, in-depth analysis of known and unknown threats, enhancing the capabilities of AWS System and Organization Controls (SOC) teams and addressing key challenges in the evolving threat landscape.
Generative AI applications should be developed with adequate controls for steering the behavior of FMs. Responsible AI considerations such as privacy, security, safety, controllability, fairness, explainability, transparency and governance help ensure that AI systems are trustworthy. In this post, we demonstrate how to use the AWS generative AI best practices framework on AWS Audit Manager to evaluate this insurance claim agent from a responsible AI lens.
In this post, we show you how Parameta used Amazon Bedrock Flows to transform their manual client email processing into an automated, intelligent workflow that reduced resolution times from weeks to days while maintaining high accuracy and operational control.
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