Healthcare AI is moving beyond individual agents performing defined tasks. Multiple agents can now work together, access information and carry out clinical and administrative workflows across different systems.
The scale of this shift is significant. IDC forecasts 1.2 billion AI agents operating globally by 2029, performing 217 billion actions every day.
Managing these systems becomes harder as the number of agents grows. An agent can act on incorrect information, pass it to another agent and trigger further actions across a workflow. All of this can happen in seconds, before anyone has time to intervene. Gartner predicts that by 2027, 40% of enterprises will demote or decommission autonomous AI agents because of governance gaps discovered after production incidents.
In healthcare, these failures can affect patient records and clinical workflows. Developers need to know what each agent is doing, how agents interact and when human approval is required. They also need a way to investigate failures and test whether the system continues to behave as expected.
This is the problem the latest expansion of Corti Agentic Framework is designed to solve. Its execution and control layer gives developers the infrastructure to coordinate agents, connect them to healthcare systems and govern their behavior without having to build and maintain these capabilities themselves.
Making complex AI systems easier to build and control
The expansion gives developers more ways to connect agents to existing software, understand what happens during a task and control how agents operate.
Connecting agents to the systems they need. An AI agent working with a patient record may need to retrieve medications, check clinical guidance and update documentation. Those tasks can involve different systems and specialized agents. Without reliable connections, agents may work with incomplete information or fail to complete the workflow. Corti provides the tools to connect these systems and coordinate the agents working across them. New connectors also let developers run certain tools within their own environments, keeping execution under their control. Streaming allows applications to display responses as they are generated.
Keeping humans in control. When multiple agents interact and trigger actions across different systems in seconds, humans cannot realistically check every action. Corti's existing guardrails allow developers to define what agents can and cannot do, while human approval mechanisms provide checkpoints for actions that require a person's decision. This gives developers control over how agents operate without requiring human intervention at every step of a complex workflow.
New capabilities also make agent behavior easier to inspect. Developers can trace which models and tools were used, check the sources behind AI-generated claims and collect feedback on individual tasks. With a record of each run, teams can assess whether agents behave as expected and investigate issues without having to reconstruct what happened.
Built for technological independence. As healthcare organizations become more reliant on AI, control extends beyond what agents do to the technology powering them. Corti's broader AI stack gives organizations the freedom to choose their models, connect to existing systems and deploy AI in their preferred environments, including on-premises, without being tied to a single provider.
For developers, that means less time building and maintaining the systems behind AI agents, and more time creating healthcare applications that meet their customers' needs.
Ready to build? Explore Corti Agentic Framework in the Console or see the new capabilities in action in our technical deep dive.
