Shadow AI discovery
80%
of workers use unapproved AI tools in their jobs.
UpGuard, 2024
AI agents, MCP servers, and model endpoints are spreading across your infrastructure faster than any team can track by hand. Every tool nobody approved is a blind spot — invisible to security, untracked by compliance, unowned by anyone.
API inventories see what is registered. Network traffic and host sensors see what is actually running. Octic combines all three.
Kernel-level sensors on servers and laptops see the AI apps, packages, and processes on each host. Network traffic analysis finds AI agents and API endpoints that never made it into any registry or API inventory.
Connects to the platforms you already run to list known AI agents, MCP servers, and API endpoints, then matches them against what the sensors and the network see.
Together, they show what an API inventory alone would miss.
The AI running in your stack, whether someone registered it or not.
Autonomous agents calling LLMs without approval
Model Context Protocol servers exposing tools and data
Unregistered endpoints serving or consuming model output
Intermediary services routing requests to LLM providers
Gateway services aggregating access to multiple models
AI workloads running outside approved infrastructure
Shadow AI breaches cost $4.63M on average — $670K more than standard breaches.
Discovery is the first step. These capabilities work together to map, track, and govern your AI stack.
Kernel-level sensors and packet analysis surface AI resources that API scanners miss. Linux and Windows hosts today.
Learn moreInteractive map of the AI agents, models, and APIs in your infrastructure, with the owner and trust state of each.
Learn moreContinuous API, network, and kernel-level discovery. The entry point to trust, observability, and remediation.
Learn moreSign up and install a sensor to see coding-agent sessions and spend, or book a demo for a walkthrough of the full control plane.
