Red Hat Formally Launches asago Open Source Project to Automate AI Governance Workflows

On August 4, 2026, Red Hat announced the launch of asago, an open-source community project developed alongside technology companies, research institutions, and academic organizations. Licensed under the Apache License 2.0, asago aims to automate the translation of corporate and regulatory AI safety policies into operational software controls. The framework connects engineering and compliance workflows into a traceable, automated system.

The Four-Stage Policy-to-Production Pipeline

The asago project—an acronym for AI Safety And Governance Orchestration—was created to convert high-level AI governance policies directly into technical enforcement mechanisms. According to Red Hat, the framework provides an automated workflow designed to shorten the timeframe required to make AI systems compliant and ready for deployment.

The architecture operates across four primary operational stages:

• Risk mapping: The platform automatically reads uploaded AI governance documents and maps specific policy clauses directly to established AI risk frameworks. Supported reference systems include the NIST AI RMF, the OWASP LLM Top 10, and the EU AI Act via the IBM AI Risk Atlas.
• Risk assessment: Rather than relying exclusively on generic benchmark tests, asago generates and runs targeted, use-case-specific safety evaluations designed to probe models and autonomous agents for harmful behaviors relative to identified risk profiles.
• Risk mitigation: Based on assessment results, the tool recommends technical guardrails and safety controls, documenting the underlying rationale to establish a clear review process.
• Production deployment: The system converts recommended safety controls into deployment-ready infrastructure configurations for live environments, eliminating manual infrastructure coding.

By connecting these four phases, asago aims to replace manual policy interpretation and custom engineering scripts with an integrated orchestration workflow.

Infrastructure Integration and Continuous Auditability

A core component of the asago project is its single-source tracing system. The software constructs a continuous audit trail that links individual clauses in a governance policy directly to corresponding safety tests and runtime controls.

According to the announcement, this tracing model provides compliance officers, software developers, system administrators, and third-party auditors with a shared interface for tracking compliance evidence.

For operational deployment, asago generates declarative configuration files compatible with standard enterprise infrastructure tools:

• Kubernetes manifest configurations for containerized runtime environments.
• Terraform scripts for cloud infrastructure provisioning.
• Ansible playbooks for automated configuration management across hybrid cloud and on-premises systems.

The project builds upon earlier collaborative efforts by Red Hat and NVIDIA under the Open Secure AI Alliance. Red Hat stated that asago complements its Lightwell initiative, which addresses vulnerabilities within open-source AI supply chains, by focusing on the operational link between policy definitions and live production agents.

Steven Huels, vice president of AI Engineering at Red Hat, detailed the focus of the initiative:

“As organizations transition from experimental AI pilots to long-running, autonomous agents, establishing clear operational guardrails becomes a critical infrastructure requirement. Through initiatives like Lightwell, we are working to secure the open source supply chain from AI-driven vulnerabilities. asago complements this effort and takes the next logical step for enterprise AI by automating the link between corporate policy definitions and live production agents.”

Founding Members and Industry Partners

The asago community was formed through a multi-organizational alliance spanning enterprise software vendors, cybersecurity laboratories, and academic institutions. Founding participants in the project include:

• Red Hat
• Alquimia AI
• Brave Software
• EvalEval coalition
• IBM Research
• Interdisciplinary Transformation University Austria (IT:U)
• Microsoft
• MIT Lincoln Laboratory
• North Carolina State University
• NVIDIA
• The Alan Turing Institute

Partner representatives outlined specific technical contributions and focus areas within the project. IBM Research is contributing testing methodologies and risk-mapping taxonomies from its IBM AI Risk Atlas to bridge gaps between compliance frameworks and deployed models.

Priya Nagpurkar, vice president of AI Platform at IBM Research, commented on the technical scope:

“To be trusted in real-world environments, AI needs measurable testing and operational controls. Through the asago community, IBM is contributing our expertise to help bridge the gap between governance frameworks and deployed AI systems.”

NVIDIA emphasized the role of open tools in securing autonomous AI agents against operational risks. Daniel Rohrer, vice president of Software Security at NVIDIA, noted:

“The Open Secure AI Alliance was founded on the principle that open models, open harnesses, and open tooling are the strongest foundation for AI defense — and asago puts that principle into practice. By automating the translation of AI governance policy into production-ready controls and audit trails, the asago project demonstrates how Red Hat, NVIDIA and our ecosystem are strengthening agent security with open source tools.”

Microsoft and Brave Software are participating to address broader ecosystem governance and user privacy. Sarah Bird, chief product officer for Responsible AI at Microsoft, highlighted the need for shared industry standards:

“Many of the hardest AI safety and security challenges are still unsolved, and no single organization can tackle them all alone. Open, widely adopted standards can help create more consistent governance across the ecosystem, while the collective ingenuity of the community can accelerate progress on the problems that matter most.”

Academic and research institutions, including MIT Lincoln Laboratory, IT:U, North Carolina State University, and The Alan Turing Institute, are bringing research in adversarial machine learning, human rights frameworks, and cybersecurity to the open-source code base.

Project Availability and Governance

The asago project is currently in its initial project formation phase. The source code and governance guidelines are published under the open-source Apache License 2.0.

Developers, academic researchers, and enterprise users can access the public code repository and participate in community governance on GitHub. Additional project details and contributor interest forms are available on the project’s official website at asago.ai.