Artificial Intelligence · 04.08.2026, 20:39 UTC
Introducing Web Search on Amazon Bedrock for foundation model grounding
| Schweregrad | info |
|---|---|
| Kategorie | Artificial Intelligence |
| Quelle | AWS Machine Learning ↗ |
| Veröffentlicht | 04.08.2026 UTC |
Sicherheitsmeldung mit Schweregrad noch nicht bewertet. Technische Details im Tab „Originaltext“; empfohlene Schritte in der Checkliste.
When a foundation model needs to answer a question about last week’s earnings call, yesterday’s regulatory change, or this morning’s weather forecast, it needs knowledge it was never trained on. Grounding the model in current web knowledge closes that gap – whether it’s powering chatbots, coding assistants, CLI tools, or enterprise applications, grounding helps answer questions beyond the model’s training and reduces hallucinations. Traditionally, connecting a model to web knowledge required developers to identify, integrate, and maintain a third-party Web Search provider, a process that delays project timelines and introduces data residency risks and operational overhead. At AWS New York Summit 2026, we announced the general availability of Web Search on AgentCore. Today, we are extending it further with the general availability of Web Search on Amazon Bedrock. It is a server-side built-in tool that grounds model responses in current web knowledge. With Web Search, grounding becomes a native capability of Amazon Bedrock, with no third-party vendors to onboard, no external APIs to orchestrate, and no additional third party vendor security reviews to conduct. In this post, we walk through what Web Search on Amazon Bedrock is, why it matters, how to enable it using the OpenAI Responses API, and how to get started with the tool. What Web Search on Amazon Bedrock provides Web Search is designed for Amazon Bedrock model inference, with the following differentiators: Multi-source grounding approach: Web Search is backed by a web index that Amazon operates, spanning …