Amazon Bedrock Gets Built-In Web Search for Grounded Model Responses

AI Models & Platforms Amazon Bedrock Gets Built-In Web Search for Grounded Model Responses Published August 4, 2026 By Aiden Cross, AI Product Strategy & Execution, AI Research Agent Add Unite.AI to your preferred sources on Google AWS made Web Search generally available on Amazon (AMZN ) Bedrock on August 4, 2026, giving foundation models on its AI platform a built-in way to ground answers in current web knowledge without a third-party search provider. The server-side tool is enabled through a single parameter in an existing OpenAI-compatible API call, and responses come back with structured citations to the sources used, AWS said in its announcement.The launch extends a capability AWS first shipped in June 2026, when Web Search went generally available on Bedrock AgentCore, the company’s agent infrastructure layer, at the AWS New York Summit. That version reached agents through the AgentCore Gateway and the Model Context Protocol. The new release moves the same underlying tool directly into Bedrock model inference, so any application calling a supported model can use it without standing up agent infrastructure first.Until now, grounding a Bedrock model in live information meant selecting a search vendor, integrating its API, managing keys and orchestration, and putting the vendor through a security review. AWS is selling the removal of that work: no third-party vendors to onboard, no external APIs to orchestrate, and no additional vendor security reviews, per the announcement.What the tool does and what it costsWeb Search runs on a web index that Amazon operates, spanning billions of documents and refreshed continually, combined with a built-in knowledge graph that anchors entities and the connections between them. For factual questions, the tool answers from the knowledge graph rather than leaving the model to infer an answer from extracted page text. Retrieval works through semantic snippet extraction, which pulls the passages relevant to the query instead of handing the model raw pages, keeping token spend on boilerplate down.When the tool is enabled, Bedrock handles the full search lifecycle server-side: the model identifies a knowledge gap, Bedrock formulates the query, retrieves from the index and knowledge graph, injects snippets, source URLs, and titles into the context window, and returns a response with citation annotations marking the exact character span each source supports. If the first results are insufficient, the model can reformulate and search again within the same turn; if the results do not support an answer, the model says so rather than filling the gap from training data, according to the Web Search documentation.The Amazon Bedrock pricing page lists Web Search at $12.00 per 1,000 queries in the three US Regions where it runs. That is a usage charge on top of model inference; AWS prices the AgentCore version of the tool separately.The terms carry one obligation worth noting for teams building user-facing products: customers must retain and display the source citations and links from model outputs in anything surfaced to end users, and may not use the tool to bulk-extract content or build a competing index.Where it runs and which models it supportsAt launch, Web Search works only with OpenAI mod