Incomplete inventory
AI tools can appear on employee devices and infrastructure before central teams know they exist.
Available now · AI discovery
Find supported AI systems operating across your enterprise.
Build an evidence-backed inventory from the endpoint outward—the first stage of Agent Interaction Observability.
Direct definition
What is AI discovery?
AI discovery identifies supported AI applications, agents, models, services, processes, and configuration evidence across an organization’s technology environment.
AxLoop knowledge base
The visibility problem
Evidence must come before control.
Disconnected signals
Devices, applications, agents, and services are often viewed in separate systems.
Unclear relationships
An application name alone does not prove which agent, model, tool, or service it used.
How AxLoop helps today
Discover from the endpoint outward.
AxLoop identifies supported AI applications, agents, local models, runtimes, and MCP configuration evidence. Each finding keeps installed, configured, running, and independently verified states distinct.
- Identify supported software and configuration evidence
- Preserve device and user scope
- Monitor meaningful state changes
Questions teams ask
- Q1Which supported AI applications are installed or running?
- Q2Where are local models and agent runtimes operating?
- Q3Which MCP servers are declared by supported clients?
Common questions
Answers, briefly.
- Why start AI discovery on the endpoint?
- Most AI adoption begins on laptops: desktop assistants, AI coding tools, IDE extensions, local models, and MCP configuration files. Cloud and network tools see only part of that picture. Starting on managed devices shows what is installed and running before it reaches a gateway or a cloud account.
- What does an AI inventory include?
- A useful inventory covers installed AI applications, running AI processes, AI CLIs and coding agents, IDE extensions, MCP clients and servers, local models, containers, and the device, user, and team context around each one. Each item carries an evidence state so teams know what was observed and when.
- How is AI discovery different from AI governance?
- Discovery answers what exists and where. Governance decides what is allowed. Without an accurate inventory, policies are written against assumptions, so discovery is the foundation that makes review, ownership, and enforcement practical.
- Does AI discovery collect prompts or source code?
- AxLoop is designed to avoid it. Discovery relies on metadata such as application identity, versions, configuration presence, and process information. Prompt content, responses, source code, and secrets are not part of the evidence model.
Agent Interaction Observability