Autonomize launches healthcare AI platform version 3

Autonomize AI has launched Version 3 of its Intelligence Platform for healthcare, which is already in production at three of the five largest U.S. health enterprises.

The new version adds deeper orchestration tools, more than 160 healthcare-focused AI agents, over 50 pre-built connectors to existing systems, and a governance framework designed to support deployment across clinical, operational and business workflows.

The launch comes as healthcare groups face pressure to reduce administrative delays in areas such as prior authorisation, claims processing, care management and clinical documentation. Autonomize argues that many providers and insurers still rely on fragmented software and manual hand-offs between departments, slowing decisions and shifting bottlenecks from one team to another.

Unified layer

Autonomize positions the platform as an operating layer that sits across existing healthcare systems rather than replacing them. It is designed to coordinate AI agents, workflows and decision-making in one environment, with connectors to electronic health records, claims systems, FHIR interfaces, and older inputs such as fax and scanned documents.

At the centre of the platform is what Autonomize calls its Knowledge Centre, which structures clinical, regulatory and coverage information into a decision-ready model. Built around a context graph containing more than 10 million concepts, it combines policy logic, real-time case information and historical decision records.

The aim is to let AI systems work across a sequence of related tasks instead of treating each request as a one-off interaction. The platform also includes a feedback loop that tracks decisions and outcomes over time, alongside governance controls intended to support compliance and audit requirements.

A Command Centre in Version 3 gives operations teams a view of business and workflow metrics across agents and processes. It also provides lifecycle tracing so users can see whether a decision was made by a human, an AI agent or a mix of both, and identify performance changes as they emerge.

Healthcare burden

The launch comes against a long-running effort across the U.S. healthcare industry to reduce the administrative burden on clinicians and staff. According to research from the American Medical Association cited by Autonomize, prior authorisation remains a major source of delays in access to care and is only one part of a wider set of manual processes that absorb staff time each week.

Healthcare organisations have spent years adding technology intended to improve efficiency, from electronic health records to revenue-cycle tools and digital services. Yet these systems often operate in separate silos, requiring staff to move data and decisions between platforms and making it difficult to manage an end-to-end process in one place.

Autonomize says its latest release is intended to address that problem by giving customers a single system in which to design, test, deploy and oversee AI-driven workflows. The platform includes an AI Marketplace with pre-built agents and workflow templates for areas including utilisation management, care management, claims and pharmacy operations.

It also includes an AI Studio, which Autonomize describes as a low-code environment for building and refining workflows using a mix of models, prompts, tools and human review. According to the company, agents are tested against real-world ground truth before deployment to check accuracy, safety and fit with operational requirements.

Executive view

Ganesh Padmanabhan, Chief Executive Officer of Autonomize AI, set out the company's view of the gap in the market.

"What's been missing in healthcare isn't AI capability, it's a system that can operate AI at scale. Until now, organizations have had to stitch together models, workflows, and governance manually, which is why so many initiatives stall before reaching production. The Autonomize Intelligence Platform V3 is the first time those pieces have been brought together into a single operational layer, where AI can reason across workflows, execute decisions, and continuously improve while ensuring the right balance between automation and human oversight," Padmanabhan said.

Autonomize says governance is embedded throughout the system through controls such as automated prompts, approvals and audit trails. It argues that this approach makes oversight part of the workflow itself rather than a separate check after a decision has been made.

The company also disclosed production use and performance figures as it seeks to position the platform in a crowded healthcare AI market. It says the system is operating at scale across three of the five largest U.S. health enterprises, with reported results including up to 55% faster clinical reviews, 60% faster decision turnaround and 30% fewer human errors.

Version 3 is available now as healthcare companies continue to test whether broader AI orchestration platforms can deliver operational gains that narrower automation tools have often failed to sustain.