Every Q4 planning cycle starts with the same board question: What AI is currently running? Most security teams answer with the list that IT approved. The real answer lives on the endpoints, in desktop AI clients, local model runtimes, coding assistants, and browser extensions that never went through review.
Airia connects to the endpoint detection and response (EDR) platforms you already run: CrowdStrike, Defender, and SentinelOne. Your existing endpoint agents become an AI discovery layer, so you can map the AI running on your endpoints before 2027 planning begins.
Your EDR already sees the AI. It just does not label it.
EDR platforms watch each endpoint for installed software, running processes, and system activity. That telemetry already holds the signs of AI adoption: a local model runtime, a desktop AI client, a developer extension that calls an external model API, an agent framework running in a terminal. Nobody asked the EDR to report on these, so they sit in a data stream built for threat hunting instead of inventory.
Airia reads that endpoint data, identifies the AI running, and records each finding in your AI inventory. The EDR connection adds device-level evidence to the signals Airia already collects from identity, network, applications, and code. One endpoint finding gets matched against the rest of that evidence instead of living in a separate console.
What your security team gets without a new rollout
Security operations teams already own the EDR. They know its deployment status, its policies, and its health across the fleet. Extending it to AI discovery means the people who run endpoint security keep running it, and the AI governance team gets a feed it did not have to build. Nobody opens a new deployment project, and nobody waits for a pilot group to install another agent.
Why Q4 is the right moment
Planning for 2027 locks in budgets, headcount, and compliance commitments. A plan built on a partial inventory inherits every blind spot in it. Airia consistently finds two to four times more AI running than organizations expect. Plans written before that gap closes get rewritten after it, and an unknown gap costs the most.
Regulatory clocks raise the stakes. The EU AI Act’s high-risk deadlines now sit at December 2027 for stand-alone systems and August 2028 for AI embedded in regulated products. SR 11-7 already applies to AI models in banking. The documentation those frameworks require takes years to build, and it starts with a complete AI inventory. Teams that start in Q4 set their own timeline. Teams that wait inherit someone else’s.
What changes when your EDR becomes a discovery layer
Coverage starts where your deployment already is. Your EDR agents already run across the fleet, so endpoint discovery does not wait on a new rollout. Airia returns a full first inventory within 24 to 48 hours and keeps it current as AI is installed, changed, or removed.
Every finding arrives with context. A bare list of applications helps nobody. Each asset carries its owner, access scope, data types accessed, and behavioral history. Risk Classifications assign a risk tier, so your team can prioritize which deployments need attention first.
No extension or SASE dependency. Airia detects shadow AI without browser extensions or SASE integration. Organizations that want broader coverage can add both, and the EDR connection fits alongside either choice.
What Airia looks for on the endpoint
Endpoint findings include desktop AI clients, local model runtimes, developer tools such as GitHub Copilot, Cursor, and VS Code extensions, and agent tooling that connects to MCP servers. Each one lands in the same AI inventory as your cloud, SaaS, and code findings, so security, governance, and finance teams all work from one record.
That matters because endpoint AI rarely stays on the endpoint. A developer’s local agent connects to an MCP server, which reaches a database that holds customer data. Seeing the endpoint is the first link in that chain.
“We already have security tools that cover AI”
Security leaders raise this objection first, and it deserves a direct answer. Your EDR is excellent at what it was built for: detecting threats on endpoints. It was not built to maintain an AI inventory, attach ownership to every AI tool, or tell you which of them touch regulated data. The EDR connection does not replace your EDR. It puts the data your EDR already collects to work on a question it never had to answer before.
From inventory to action
You cannot secure what you have not found, prove governance you have not enforced, or optimize what you cannot measure. The inventory Airia builds is the foundation of our platform. Airia’s security capabilities enforce policy against it, our governance capabilities generate audit-ready documentation from it through compliance reporting, and our optimize capabilities track its cost and performance. All four work from the same data, with no exports and no reconciliation between tools.
Each team gets something concrete. The Airia platform identifies AI that skipped review and can act on it the day it appears. Compliance gets an inventory built from system data instead of manual attestation. Finance sees the duplicate tools that business units adopted on their own.
A practical Q4 plan
Start with three moves. Connect your EDR platform to Airia. Compare the first inventory against your approved AI list and sort the gap by risk tier. Then carry that inventory into your 2027 plan as the baseline for security controls, compliance documentation, and AI spend.
Ask your EDR administrators one question along the way: which endpoints does the EDR not cover? Gaps in EDR coverage become gaps in endpoint discovery, so closing them strengthens both programs. Unmanaged and contractor devices deserve a plan of their own, and the rest of Airia’s signals help there.
Teams that do this in Q4 walk into planning season with facts. The budget conversation shifts from estimates to an attributed inventory, and the board question gets an answer built from your own endpoints.
Discover what your endpoints are running
Your EDR has been collecting the evidence for months. Put it to work before the planning cycle closes. Request a demo and see what is running across your endpoints today.
Put these ideas to work.
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