Airrived launches observability for enterprise AI agents

Airrived has launched Agentic Observability for its enterprise Agentic OS, aimed at companies deploying autonomous AI agents.

The feature is designed to help organisations monitor how AI agents behave, from data ingestion to resulting actions, as businesses move beyond limited pilots and begin running larger networks of automated systems.

Agentic Observability extends Airrived's existing software with a control layer that shows who created an agent, who owns it, what permissions it has and whether human approval is required before it acts. The system also tracks the data agents touch and links their activity to operational results.

The launch comes as companies face growing scrutiny over how they govern AI tools that can make decisions and execute tasks with limited human intervention. That has pushed monitoring and internal controls higher up the agenda for security, compliance and technology teams.

Governance focus

Airrived argues that traditional software monitoring is not enough for systems that can reason, decide and act on their own. In response, it has built the product around what it describes as a full trace of the agent workflow, from source data to business outcome.

At the centre of that approach is Airrived's Context Lake, which brings together data and operational context from across enterprise systems. This allows customers to trace how data moves through agentic applications and understand the link between an AI-driven decision and a later operational event, such as a security alert or root-cause finding.

The vendor is also emphasising permissions and ownership, two issues that have grown in importance as more organisations test AI agents in live business settings. The product is designed to show strict access boundaries around each agent and whether a human reviewer must approve a step before it is completed.

Another focus is data risk. Users can track the movement of sensitive information, including personally identifiable information, payment card data and protected health information, across agentic workflows.

The product also includes cost tracking for token use and model consumption, an area companies often describe as difficult to measure once AI use expands across departments. The reporting is intended to give finance and operations teams clearer accountability over spending tied to AI systems.

Anurag Gurtu, co-founder and chief executive officer of Airrived, set out the company's view of the shift underway in enterprise software. "Enterprises are moving from software that executes instructions to agents that reason, decide, and act," Gurtu said.

He added: "You cannot govern what you cannot see. Agentic Observability gives enterprises visibility from data, to decision, to action, to outcome."

Market shift

The launch reflects a broader change in how software suppliers are framing AI management tools. Earlier enterprise AI products often focused on chatbot access, model performance or basic usage analytics. A newer wave of tools is trying to address the operational risks that emerge when software agents can take actions across business systems, including making changes, handling requests or triggering downstream processes.

For buyers, that changes the questions they need to answer internally. Instead of asking only whether an AI system works, companies increasingly need to know which person or team is accountable for a given agent, what systems it can access, what data it handles and how much it costs to run.

Airrived is positioning its software around those concerns in cybersecurity, IT and wider enterprise operations. Its platform supports on-premises deployments, private infrastructure and fully air-gapped environments, suggesting it is targeting organisations with strict security or data residency requirements as well as mainstream enterprise users.

Gurtu also framed the issue in terms of internal accountability and control over AI systems. "Agentic AI cannot become a black box running inside the enterprise," he said.

He continued: "Every agent needs an owner. Every action needs a permission. Every sensitive data interaction needs visibility. Every dollar of AI consumption needs accountability."