Announcing Web Search on Amazon Bedrock AgentCore: Ground your AI agents in current, accurate web knowledge

One of the biggest challenges when deploying AI agents in production is keeping them accurate. Language models have knowledge cutoffs—they don’t know about events after their training data ends. If your customer service agent is answering questions about your latest product launch or an agent needs real-time pricing information, it’s working with stale information. AWS is addressing this with Web Search on Amazon Bedrock AgentCore, a managed capability that lets your agents pull current information directly from the web without you having to build and maintain the infrastructure yourself.

Here’s what’s happening under the hood. When you enable Web Search on AgentCore, your agent gains access to a fully managed search capability that integrates seamlessly into the agent’s decision-making loop. When your agent decides it needs current information to answer a user query, it automatically performs a web search, processes the results, and includes citations in its response—all within your AWS environment. This matters because the search happens in your secure boundary; there’s zero data egress to external services. Your customer queries and the agent’s reasoning stay inside AWS. The agent uses these fresh, cited sources to ground its responses, reducing hallucinations and improving accuracy on time-sensitive topics.

From a practical standpoint, this removes significant operational burden. Previously, if you wanted web-aware agents, you’d either build custom integrations with search APIs (handling rate limits, result parsing, and error handling yourself) or use general agent frameworks and manage the infrastructure complexity. Now you focus on defining what your agent should do—its goals and tools—while AWS handles the web search execution. Real-world scenarios include support agents answering questions about current promotions, financial advisory agents retrieving latest market data, or research assistants pulling recent news and documentation. For teams still building their AI skills, this is especially valuable because it abstracts away the infrastructure piece and lets you concentrate on prompt engineering, tool design, and agent workflows.

The key advantage is simplicity with security baked in. Your team doesn’t maintain web search infrastructure, and your data doesn’t leave your AWS environment. If you’re already using Bedrock AgentCore, adding Web Search is a configuration step rather than an architectural redesign. For organizations deploying agents to production, this is a meaningful step toward making them reliably accurate without becoming a DevOps project.