The Linux Foundation (LF) has announced two open-source initiatives designed to strengthen trust in enterprise AI. One extends the Domain Name System (DNS) to provide verified identities for AI agents, while the other provides an open framework for assessing AI systems against emerging global standards.
The first initiative, Agent Name Service (ANS), builds on existing DNS infrastructure to provide trusted identity, verification, and discovery for AI agents operating across the internet. The second initiative, the Appia Foundation, establishes standardized assessment frameworks for agentic safety and accountability.
ANS enables portable identity, verification, and discovery for the emerging agentic web. The framework allows systems operators and users to verify who an agent represents, what permissions it has, and whether its code and operational history remain authentic and unchanged.
As AI agents rapidly move from experimentation into production systems, organizations face growing challenges around authentication, trust, governance, and interoperability. According to the World Economic Forum, 82% of executives plan to adopt AI agents within the next one to three years, despite widespread uncertainty about how to securely evaluate and manage autonomous systems.
ANS addresses this gap by extending the same infrastructure that already powers the web today, creating a verifiable identity layer for the agentic era. It does not rely on proprietary registries or centralized control.
LF CEO Jim Zemlin noted that AI agents will increasingly operate across enterprises, platforms, and digital services, making trusted identity infrastructure a foundational requirement.
“By building on DNS and open standards, ANS creates a scalable and interoperable framework for verified agent communication across the global digital economy,” he said.
Building on Internet Infrastructure
DNS, the internet's globally distributed naming system, already processes more than 100 million queries per second worldwide. The ANS framework allows systems and users to verify an agent's full operational status. It also supports decentralized identifiers (DIDs) and Legal Entity Identifiers (LEIs), enabling organizations to integrate existing identity systems into a unified verification model.
"The success of the internet didn't come from proprietary systems. It came from open standards, shared infrastructure, and an ecosystem committed to working together,” said Jared Sine, chief strategy and legal officer of GoDaddy.
Building on proven internet infrastructure, ANS helps identify and discover agents across the open web. This helps ensure the next era of innovation remains as open and interoperable as the last, he added.
Backers include Cloudflare, Cisco, Salesforce, GoDaddy, and Infoblox.
Supporters say ANS builds on DNS, one of the internet's most established trust layers, extending it to a world where AI agents need to be discovered, verified, and understood across multiple systems.
Michael Kantor, president at registry broker firm Hashgraph Online (HOL), observed that AI agents are quickly becoming active participants in digital business. This means they need identity infrastructure that is open, portable, and built for the internet itself.
"HOL believes the next phase of the internet will depend on shared standards that let agents move across protocols and ecosystems without creating new silos. ANS is a meaningful step toward that future," he said.
Together, the initiatives address two emerging enterprise AI challenges: establishing trusted identities for autonomous software agents and creating consistent methods for evaluating AI systems.
LF announced ANS on June 23 but did not specify when the project would become available.
LinuxInsider asked an LF media representative when ANS would launch and what was involved in preparing a new open-source standard for release. The spokesperson said only that ANS is expected to launch in the coming weeks.
New Appia Foundation Bridges Global AI Value Chain Standards
Alongside ANS, the Linux Foundation also launched the Appia Foundation, a separate initiative focused on helping organizations assess and demonstrate the trustworthiness of AI systems. Founding members include Armilla AI, Arm, Ericsson, Google, Mastercard, Microsoft, Mitsubishi Electric, Naaia, Nemko, Omron, OpenAI, Schneider Electric, and Siemens.
The Appia Foundation, hosted by the Joint Development Foundation (JDF), provides an open, connecting layer that builds on international standards to develop publicly available global specifications.
The Appia specifications, organized into a requirements and guidance layer and an assessment enablement layer, provide the testing criteria, evaluation guidelines, and component typologies needed to effectively assess AI models, systems, applications, and processes.
Zemlin said global organizations need a consistent, practical way to verify that AI systems conform to new expectations. The Appia Foundation creates a neutral environment where the entire industry can collaborate on a common assessment framework.
"By building this infrastructure in the open, we are helping organizations reduce complexity, lower operational costs, and build trust," he told LinuxInsider.
Creating a Common Assessment Framework
Craig Shank, executive director of the Appia Foundation, added that AI systems now make decisions about people's loans, their children's schools, and their jobs. People on the receiving end deserve to know those systems were built and assessed against criteria that hold up to scrutiny.
“The Appia Foundation was formed to do that work: creating publicly available specifications that organizations across the AI value chain use to demonstrate their systems meet those criteria," he said.
"By establishing this open framework, we are building the accountability layer required to scale safe and trusted AI across major industries.”
Nathalie Beslay, CEO and founder of Naaia, an AI governance and trust advisory firm, maintained that trustworthy AI cannot remain a promise. It must become an architecture. This initiative builds the common foundation to turn regulations and standards into verifiable assessments across the AI value chain.
"Building trustworthy AI is one of the defining challenges of our era, and it calls for a shared, global answer: one modular framework of trust that holds across every jurisdiction, every standard, every actor in the AI value chain," she said.
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