AWS brings multi-agent orchestration to Bedrock

AWS is doubling down on AI agents with the announcement of multiagent capabilities on its Amazon Bedrock platform. 

During his keynote at the AWS re:Invent conference, AWS CEO Matt Garman said customers building agents on Bedrock wanted a means to make agents that work together. 

“While a single agent can be useful, more complex tasks, like performing financial analysis across hundreds or thousands of different variables, may require a large number of agents with their own specializations,” Garman said. “However, creating a system that can coordinate multiple agents, share context across them, and dynamically route different tasks to the right agent requires specialized tools and generative AI expertise that many companies do not have available.”

The new capabilities allow enterprises using Bedrock to build agentic workflows to build AI agents and establish their entire agentic ecosystem. This includes the ability to build orchestration agents to manage multiple agents and workflows that require multiple steps. 

AWS’s emphasis on agent collaboration differentiates from the approach taken by Microsoft in its announcements around multi-agent support two weeks ago. AWS’s approach builds on its extensive experience with microservices. In an interview with VentureBeat, Swami Sivasubramanian, VP, AI and Data, AWS said the company got key insights from developing its Q dev agent, which he says is best-in-class on the SWE benchmark, which is based on real-world engineering tasks. That background shaped the tools being introduced today, he said. This production-ready focus allows enterprises to move from prototype to deployment faster, he said, with orchestration capabilities that streamline workflows, manage state sharing, and dynamically allocate tasks across specialized agents. These features differentiate AWS from competitors like Microsoft, he said, whose agent tools prioritize broader frameworks but lack the same level of orchestration focus and deployment readiness.

“Using multi-agent collaboration in Amazon Bedrock, customers can get more accurate results by creating and assigning specialized agents for specific steps of a project and accelerate tasks by orchestrating multiple agents working in parallel,” AWS said. 

Customers build their specialized agents on Bedrock, and then make a supervisor or orchestrator agent to help manage the other agents. AWS said the supervisor agent “handles the coordination, like breaking up and routing tasks to the right agents, giving specific agents access to the information they need to complete their work and determining what actions can be processed in parallel.”

Once the other agents finish their tasks, the orchestrator agent then pulls all that information together. Garman pointed to Moody’s, the credit rating agency and one of its customers that first used the multiagent capability. Moody’s created a series of agents for its risk analysis workflow. The company created agents that analyzed macroeconomic trends or looked at the risks of companies, which were able to build more accurate risk assessments.

AWS first introduced agentic capabilities in 2023 with the release of Agents on Bedrock, which offered enterprises a way to start building agents. During its re:Invent event this week, AWS customers like PagerDuty and GitLab announced new agents that let users develop their applications on their platforms and use AWS agents to enhance their workflows. 

Multiple agents becoming the norm

Enterprises turn to agents to help simplify their workflows, so having an agentic ecosystem with multiple AI agents is fast becoming popular, and service providers have noticed. Microsoft offers a library of agents for Copilot users (and has amassed one of the largest agent ecosystems). ServiceNow also has a suite of AI agents, making its orchestrator agent a big selling point. Even OpenAI understands the growing appeal of AI agents with its Swarm AI agent framework. 

However, enterprises also need to control the sprawl of AI agents and make sure the agents actually do their job for the task. The orchestration layer, often consisting of an orchestrator agent, monitors the task progress and triggers which agent will start working next. 

AWS’s approach is to allow enterprises to build the complex multiagent workflows they want and the orchestration layer they need. Other providers, like ServiceNow and Salesforce, give customers access to the agents, which can be customized to their needs, and then offer orchestrator agents built by the company. 

Managing AI agent sprawl is the next big step in the agentic wars, and the space is heating up.