Red Hat, Inc., a company that produces enterprise software solutions under open-source license, has introduced asago, an open-source community effort to develop automated tools for the translation of AI governance guidelines at the high level into production-ready systems.
Asago creates an auditable end-to-end process by connecting tools, compliance requirements, and engineering practices. The solution is designed to eliminate the conflict between compliance and development teams and facilitate the safe transition of enterprises from AI experiments to production systems within days, not months.
What is Asago?
Asago (AI Safety And Governance Orchestration) establishes a standardized open-source platform designed to translate corporate governance policies and global regulatory mandates directly into operational software controls. Building upon Red Hat and NVIDIA’s joint contributions within the Open Secure AI Alliance, the project aligns developer agility with operational compliance across four core lifecycle phases:
The audit logs generated during each stage map the regulatory requirements to the automated test cases and runtime controls. The result is better granularity and predictability of how to turn AI safety into an enterprise utility.
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Addressing the Tension Between Innovation and Compliance
One of the biggest bottlenecks in adopting AI in enterprises is bridging the disconnect between compliance regulations and software settings. The manual back-and-forth between risk officers and DevOps engineers causes delays and increases the chance of misunderstanding.
In light of the new requirements, for example, the EU AI Act, enterprises find themselves in a lose-lose situation – either operational paralysis from months of manual reviews, or security risks from uncontrolled shadow AI deployments.
Asago resolves this operational gap by establishing a shared, open standard across compliance teams, data scientists, and infrastructure engineers. By incorporating every stakeholder into a unified workflow, the platform implements automated safety guardrails for autonomous AI agents and enterprise large language models (LLMs) without the overhead or errors of manual policy translation.
“As organizations transition from experimental AI pilots to long-running, autonomous agents, establishing clear operational guardrails becomes a critical infrastructure requirement,” said Steven Huels, vice president, AI Engineering, Red Hat. “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. This gives enterprises the end-to-end operational confidence they need to scale trusted AI across the hybrid cloud.”
“The asago project is a true collaborative, open source endeavour bringing together stakeholders from the technology industry, academia and government,” said Stuart Battersby, AI safety and model evaluation architect, Red Hat. “We encourage more collaborators to join this community driven effort, particularly from global jurisdictions, to ensure maximum coverage of AI safety viewpoints.”