“We’re being asked to adopt AI, secure it, and defend against the threats it enables. We didn’t even know how to start. It’s like a firehose. Zaun solved that.”
The problem
The question is no longer whether to allow AI. It's whether security sees it happen or reads about it later in an incident report. A developer can install Claude Code & Cowork and ship to production the same day, while the request to evaluate it sits in a review queue. The teams pulling ahead stop trying to slow adoption down and engineer a path to safe acceleration. Zaun calls this AI Adoption Security: one loop, from the first trace of shadow AI through live detection and response, each pass faster than the last.
One loop, four stages
Reagent runs adoption as a single loop rather than a one-time gate. Here is how it ran at Audubon.
01See
AI was already in the building: developers in Claude Code & Cowork, staff signing into AI apps through their identity provider. Reagent's discovery mesh mapped the real footprint from the telemetry Audubon already had, across OAuth, network, cloud, and endpoint, with nothing new to install. It surfaced shadow AI use the team had never seen, identifying 27 unsanctioned tools.
02Decide
Legacy third-party risk maps a vendor to a framework and hands back a grade that scores the vendor in the abstract, not what the tool does to the controls you run. Reagent assessed Claude Code & Cowork against Audubon's own controls, threat-modeled it, and produced a vendor-facing list of conditions reviewed line by line.
Clearing one tool with real conditions attached leaves a reusable control lens that makes the next tool of its kind faster to assess. Governance stops being a binder and becomes a composable framework.
03Enforce
Approval is the start, not the end; the hard part is making the approved policy hold at runtime. Reagent compiles the conditions into live policy and checks every tool call an agent makes and every CLI command Claude Code & Cowork runs against it before the call executes, not after it surfaces in a log.
When a call falls outside policy, Reagent does not just flag it. It enforces through the controls an organization like Audubon already runs, at the layer that can actually stop the action: identity through IdP, the endpoint through EDR, and network appliances. One decision, pushed to whichever plane owns the action, even when the AI tool ships no permissions of its own.
04Detect & respond
A dashboard proving an agent behaved all quarter is worth little; the problem is the one that doesn't. ABBA, Zaun's Agent and Bot Behavioral Analytics, learns each identity's baseline and explains deviations in plain language. When a service agent spikes its sign-in rate, appears from new IPs, and assumes a role it has touched exactly never, Reagent ties identity, cloud, and endpoint into one timeline and contains it live: keys rotated, session revoked, role binding pulled, host isolated. The machine contains; a person judges.
Reagent keeps cost down by filtering with semantic matching and clustering before any LLM classification runs, so the expensive model only sees what truly needs it, with no loss in coverage.
Why it compounds
Each pass sharpens the next. Every assessment refines the control lens; every baseline learned for one agent sharpens detection for the next. Governance that used to sit in a binder and rot becomes capability that compounds, which is why the program speeds up over time instead of collapsing under its own weight.
Audubon is already onboarding five more AI tools next quarter, with more to follow, each faster to clear than the last. The organization that adopts AI at the speed the technology moves stays ahead of the risk; the one that can't keeps learning about its own AI from the incident report. Security stops being the reason adoption stalls and becomes the reason it moves fast without breaking.
Make security the reason AI moves fast.
If your team is approving AI faster than it can see it, let's talk. A 30-minute call, no slideware.