Category: Featured

The Llama 3.1 models are a collection of 8B, 70B, and 405B parameter size multilingual models that demonstrate state-of-the-art performance on a wide range of industry benchmarks, offering new capabilities for your generative AI applications.

Store, index, retrieve, and search vectors with in-memory performance for use cases like retrieval augmentation, semantic caching, and anomaly detection through single-digit millisecond queries.

Effortlessly build apps with AI-powered low-code tools, enabling organizations to create secure custom apps in minutes without dev teams – streamlining processes like claims, inventory, and approvals.

Craft generative AI apps from conversations using natural language and approved data sources. Customize securely shared apps, specifying data sources per card and new APIs for programmatic app management.

Unlock hyper-relevant code suggestions tailored to your codebase; enhance productivity with Amazon Q Developer’s private customization while maintaining robust data privacy and security standards.

Agents for Amazon Bedrock now offer Memory to retain user context and Code Interpreter to dynamically execute code snippets—whether for data analysis, visualization, or complex problem-solving.

Guardrails for Amazon Bedrock adds hallucination detection and an independent API to fortify generative AI applications with customized guardrails across any model, ensuring responsible and trustworthy outputs.

Enhance company knowledge bases with new Amazon Bedrock connectors for Confluence, Salesforce, SharePoint, and web domains – empowering RAG models with contextual data for more accurate and relevant responses.