Ask a security leader what AI the organization runs, and the answer on day 1 is usually a list of approved tools plus a hunch that the real number is larger. The hunch is right. Airia consistently finds two to four times more AI than organizations expect. The question is how fast you can replace the hunch with a record.
The Airia Discovery Engagement does that in 21 days, at a fixed price of $7,995. It is built on Airia Discover, and it ends with three deliverables your team can act on. Here is what changes between day 1 and day 21.
Day 1: a list, a hunch, and partial records
On day 1, security, IT, and governance each hold part of the picture. The approved list covers what went through procurement. It misses agents built in Copilot Studio and n8n, LLM calls buried in application code, AI features that a SaaS vendor enabled by default, and local tools that employees installed themselves, sometimes under personal accounts on company hardware.
Those records disagree with each other, and none of them is current. Decisions built on them carry the same gaps, which is how an organization ends up with security controls, compliance documentation, and budgets that cover only part of what runs.
None of this reflects carelessness. AI adoption follows the pattern cloud adoption did: rapid, distributed, and ahead of any central governance function. The gap is structural, which is why a one-time survey or a spreadsheet never closes it.
Setup: three tasks for your team
The engagement asks little of you by design. You provide a read-only, low-permission service account with no elevated privileges. You authorize deployment of the endpoint agent and browser extension through your existing MDM. Later, you attend the readout.
Airia handles the rest. We connect and configure your identity provider, guide the endpoint and browser deployments, configure network signal routing where it applies, and monitor, aggregate, and analyze every discovery feed. Discover returns a first inventory within 24 to 48 hours of deployment and keeps it current from there.
Discovery: signals that see different layers
AI that bypassed review shows up in different places depending on how it arrived, so the engagement combines signals. Each one sees a layer the others miss.
Native endpoint agent. An MDM-deployed background agent finds installed AI applications such as Cursor, Claude Desktop, and Ollama, along with MCP servers on the device, local AI runtimes, and coding assistants. It catches AI that lives entirely on the machine, including personal-account use on company hardware.
Identity platform. A read-only connection maps every AI app accessed through corporate single sign-on by user, tool, and frequency. It takes a single admin task, and it keeps the inventory current as people sign in to new tools.
Browser extension. The extension captures AI usage at the browser session level, including personal logins and direct URL access that never touch your identity provider. It also lets you block or redirect usage.
Network, code, and agent platforms. Network-level routing inspects AI model traffic. Code scanning finds AI framework dependencies and direct LLM API calls in repositories. External agent integrations show what runs on orchestration platforms such as n8n and Copilot Studio. Airia recommends starting with the endpoint, identity, and browser signals, and adding the others based on your footprint. Together they feed one AI inventory.
Day 21: three deliverables
The engagement closes with a readout, where Airia presents the findings and you decide what happens next. You leave with three things.
A Verified AI Inventory. It catalogs the AI tools, models, APIs, MCP servers, and automations the engagement discovered, organized by signal source, user, and risk category. It replaces the competing partial lists with one record.
A Risk and Posture Assessment. Confidence-scored ratings cover the AI landscape and flag critical data exposure, compliance gaps, and audit failure risks. The ratings follow the same approach as Risk Classifications, so the tiering carries forward if you continue on the platform.
A Prioritized Analysis. A board-ready report ranks your highest-priority AI risks and lays out a clear path forward. It is written for executive and audit committee audiences, so it travels without translation.
The first inventory usually points in three directions at once. Shadow AI with access to enterprise data creates immediate demand for runtime enforcement. Undocumented deployments create demand for governance evidence. Duplicate tools across business units create demand for spend management. The readout ranks these findings so you see where to start.
What your security team knows on day 21 that it did not on day 1
On day 1, the team knows what it approved. On day 21, it knows what is running, who owns it, what it can access, and which deployments deserve attention first. It can answer a board member or an auditor with a record instead of an estimate. It also knows which agents carry the most exposure, so the first dollars go where they reduce the most risk.
Compliance teams gain a starting inventory for EU AI Act, NIST AI RMF, and SR 11-7 work. Finance gains a view of duplicate tools across business units. Engineering gains a clear picture of the AI embedded in its own code.
Who gets the most from 21 days
The engagement fits organizations preparing for a regulatory audit that need a current inventory built from system data, and teams that inherited AI through an acquisition and never inventoried it. It also fits security teams that tried a manual inventory and know the result is incomplete, CISOs whose board or regulator asked for an inventory they cannot yet produce, and organizations with active developer communities or broad SaaS AI adoption that nobody reviewed.
What the engagement is, and what it leaves open
The Discovery Engagement is a fixed-scope, 21-day engagement at a fixed price. It carries no long-term access commitments, and it does not require a platform decision. The readout gives you evidence, and you choose the next step.
When you choose to continue, the inventory is already in place. Secure enforces policy against it, Govern applies policy and documentation to it, and Optimize tracks cost and performance, all from the same record. Teams can review how that continuation works in compliance reporting and the rest of the platform.
Discover your day 21 view
You cannot govern AI you have not found, and 21 days is a short distance between a hunch and a record. Request a demo of Airia Discover and ask about the Discovery Engagement.
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