AI agents are changing how organizations find and act on information, but they share one structural limitation: their knowledge is frozen at training time. When you ask an agent that relies only on its training data about today’s stock price, a sports score, or a release that shipped an hour ago, it can’t respond. Web …
Introducing Web Search on Amazon Bedrock AgentCore Read More »
Amazon Quick and Adobe Marketing Agent help marketing teams access campaign insights within governed conversations in seconds. Marketers can ask questions about campaign performance, audiences, journeys, campaign conflicts, and content performance in natural language. Amazon Quick provides the chat experience and action orchestration. Adobe provides marketing-domain analysis to the approved data sources behind those questions. …
Accelerate campaign workflow with insights from Adobe Marketing Agent for Amazon Quick Read More »
Monitoring and troubleshooting generative AI inference endpoints operating at scale is challenging. When your large language model (LLM) endpoint’s P99 latency spikes, you must determine in minutes whether the root cause is GPU memory pressure, a saturated KV cache, unbalanced traffic across Availability Zones, or an auto scaling policy that hasn’t triggered. The shift from …
A year ago, Simon Willison wrote one of the cleanest definitions of an agent that has stuck around: An LLM agent runs tools in a loop to achieve a goal. That definition stuck because it describes what every production agent actually does. Kiro, Amazon Q Developer, Quick Agents, Codex, Claude Code: under the hood, they …
Today, we’re announcing inline payload support for Amazon SageMaker AI Async Inference. Customers can now send inference payloads directly in the request body of the InvokeEndpointAsync API, removing the need to upload input data to Amazon Simple Storage Service (Amazon S3) before each invocation. For payloads up to 128,000 bytes, this removes an entire network …
Amazon SageMaker AI Async Inference now supports inline request payloads Read More »
What if you came back from a full day of meetings and the busywork was already done? Stalled deals followed up on. Compliance changes summarized. Meeting prep written. Not because you multi-tasked, but because something was working in the background while you focused on other urgent priorities. Teams are already using Amazon Quick — an AI assistant that connects to your most-used apps …
Get back hours every day with autonomous agents in Amazon Quick Read More »
Agents are only as intelligent as the context they can reason over. Today, that context is scattered across data lakes, data warehouses, lakehouses, databases, and streams, and in institutional knowledge that has never been written down. You want to trust the decisions made by your AI agents, but that can’t happen until agents have context. Imagine what becomes possible …
Context intelligence for your data and AI agents at scale Read More »
The models powering today’s agents are remarkably capable. They can reason across complex problems, plan multi-step workflows, and generate nuanced responses. But most agents are operating well below that potential. The gap isn’t intelligence. It’s access to the right context and feedback. A customer service agent tasked with answering a question about your company’s refund …
Research in “Nature” shows our conversational AI system matches primary care physicians in complex disease management.
Today, we’re announcing a new API with Amazon Bedrock Guardrails. With this API, you can apply individual safeguards, also referred to as safety checks, at any point in your agentic AI applications without creating guardrail resources. The new InvokeGuardrailChecks API gives you the flexibility to invoke supported safeguards at any turn in the agentic loop …
