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1. Meeting summarization and action item extraction with Amazon Nova

   In this post, we present a benchmark of different understanding models from the Amazon Nova family available on Amazon Bedrock, to provide insights on how you can choose the best model for a meeting summarization task.

2. Building a custom text-to-SQL agent using Amazon Bedrock and Converse API

   Developing robust text-to-SQL capabilities is a critical challenge in the field of natural language processing (NLP) and database management. The complexity of NLP and database management increases in this field, particularly while dealing with complex queries and database structures. In this post, we introduce a straightforward but powerful solution with accompanying code to text-to-SQL using a...

3. Accelerate threat modeling with generative AI

   In this post, we explore how generative AI can revolutionize threat modeling practices by automating vulnerability identification, generating comprehensive attack scenarios, and providing contextual mitigation strategies.

4. How Anomalo solves unstructured data quality issues to deliver trusted assets for AI with AWS

   In this post, we explore how you can use Anomalo with Amazon Web Services (AWS) AI and machine learning (AI/ML) to profile, validate, and cleanse unstructured data collections to transform your data lake into a trusted source for production ready AI initiatives.

5. An innovative financial services leader finds the right AI solution: Robinhood and Amazon Nova

   In this post, we share how Robinhood delivers democratized finance and real-time market insights using generative AI and Amazon Nova.

6. Build conversational interfaces for structured data using Amazon Bedrock Knowledge Bases

   This post provides instructions to configure a structured data retrieval solution, with practical code examples and templates. It covers implementation samples and additional considerations, empowering you to quickly build and scale your conversational data interfaces.

7. How Apollo Tyres is unlocking machine insights using agentic AI-powered Manufacturing Reasoner

   In this post, we share how Apollo Tyres used generative AI with Amazon Bedrock to harness the insights from their machine data in a natural language interaction mode to gain a comprehensive view of its manufacturing processes, enabling data-driven decision-making and optimizing operational efficiency.

8. Extend your Amazon Q Business with PagerDuty Advance data accessor

   In this post, we demonstrate how organizations can enhance their incident management capabilities by integrating PagerDuty Advance, an innovative set of agentic and generative AI capabilities that automate response workflows and provide real-time insights into operational health, with Amazon Q Business. We show how to configure PagerDuty Advance as a data accessor for Amazon Q indexes, so you...

9. Innovate business logic by implementing return of control in Amazon Bedrock Agents

   In the context of distributed systems and microservices architecture, orchestrating communication between diverse components presents significant challenges. However, with the launch of Amazon Bedrock Agents, the landscape is evolving, offering a simplified approach to agent creation and seamless integration of the return of control capability. In this post, we explore how Amazon Bedrock Agents...

10. Deploy Qwen models with Amazon Bedrock Custom Model Import

    You can now import custom weights for Qwen2, Qwen2_VL, and Qwen2_5_VL architectures, including models like Qwen 2, 2.5 Coder, Qwen 2.5 VL, and QwQ 32B. In this post, we cover how to deploy Qwen 2.5 models with Amazon Bedrock Custom Model Import, making them accessible to organizations looking to use state-of-the-art AI capabilities within the AWS infrastructure at an effective cost.