Tag: Amazon Bedrock

BMC’s HelixGPT, combined with Amazon Web Services, can transform IT operations by reducing Mean Time To Repair (MTTR) and enhancing decision-making processes.

Hyper-personalization is transforming digital marketing and enhancing customer experience. This blog post explains how the Braze customer engagement platform, augmented by Amazon Web Services (AWS) Generative AI services, revolutionizes your brand-customer interactions. By integrating Braze with AWS’s advanced AI capabilities, you can forge more meaningful, real-time connections with your customers. Using Amazon Bedrock, Braze creates highly personalized content that adapts to your customers’ individual preferences and behaviors in real time. This approach facilitates tailored messaging, recommendations, and interactions that resonate deeply with each user, driving immediate engagement, long-term loyalty, and revenue growth. In this post, we’ll explore how strategically integrating Braze and AWS transformed customer engagement strategies, fostering a more personalized and profitable customer journey.

As organizations rapidly adopt generative AI models in enterprise workflows, they face increasing security risks such as prompt injection attacks, model poisoning, and data extraction vulnerabilities. This blog demonstrates how Protect AI’s Guardian and Recon tools integrate with Amazon Bedrock to secure DeepSeek model deployments.

This blog post shows how Infor uses generative AI services on Amazon Web Services (AWS) to help customers speed up productivity and solve industry-specific challenges

In today’s fast-paced digital landscape, the integration of AI in DevOps is changing how organizations balance innovation with compliance requirements. Generative AI tools have enhanced developer productivity, with estimates suggesting up to 45% improvement in efficiency, while creating new challenges for quality control and regulatory compliance. Through solutions like SpiraTeam from Inflectra, organizations can now leverage AI to modernize their quality and compliance processes while maintaining rigorous safety standards, particularly crucial for regulated industries like healthcare, finance, and utilities.

Tresle.ai, using over 49 AWS services, delivers a complete generative AI platform that enables businesses to harness AI capabilities for personalized recommendations, content generation, and data insights. With advanced vector search technology at its core, the platform makes it effortless for companies to integrate AI into their applications and uncover meaningful relationships across diverse datasets.

In the rapidly evolving landscape of Generative AI (GenAI), Orkes Conductor emerges as a powerful orchestration platform that helps organizations manage complex workflows, integrate with AWS services, and implement essential safeguards for GenAI applications. The platform offers pre-built LLM tasks, robust error handling, and monitoring capabilities, enabling developers to create sophisticated AI workflows while providing enterprise features like RBAC, audit logs, and versioning for supported applications.

Learn how an AWS Advanced Technology Partner, Langfuse, offers an open-source LLM engineering platform that helps developers monitor, debug, analyze, and iterate on their LLM applications. Langfuse LLM engineering platform helps enterprises gain visibility into their LLM applications while seamlessly integrating with Amazon Bedrock and other popular AI frameworks.

Adobe Experience Platform, AWS, and Merkle’s Bring Your Own Model (BYOM) accelerator are transforming customer experience personalization at scale. This integration combines AEP’s data foundation, AWS’s enterprise AI capabilities, and Merkle’s ML model integration to deliver highly targeted customer experiences. The solution enables organizations to reduce implementation costs by 60% while leveraging custom ML models and generative AI for enhanced customer engagement

In this post, we explain how Dynatrace provides end-to-end monitoring and visibility into generative AI applications utilizing Amazon Bedrock models allowing for comprehensive LLM observability.