Discovery

Shadow AI Discovery

Find every AI app, model, and browser extension in use across your workforce — including off-network laptops and locally-run models.

In short

Shadow AI discovery is the process of building a complete, attributed inventory of every AI tool, model, and extension in use across an organisation — including those never approved by security. KavachLab discovers AI usage from four vantage points simultaneously — endpoint, browser, network, and cloud — because no single vantage sees everything. The endpoint agent catches locally-run models and off-network laptops, the browser extension sees the actual prompts and uploads, network sensors provide breadth across managed traffic, and cloud connectors capture server-side and SaaS AI usage.

What it gives you

Local and off-network models
Detects Ollama, LM Studio, and other local runtimes that never touch your network — the blind spot network-only tools cannot close.
Prompt-level fidelity
Sees the actual prompt, upload, and generated output rather than inferring intent from a domain name.
Attributed to a user
Every interaction is tied to an identity, device, and business unit, so exposure can be measured and owned.
Behaviour-based detection
New tools are found by how they behave, not by an allowlist, so coverage does not lag each new model release.

Why network-only discovery misses most Shadow AI

Tools that rely purely on DNS, proxy, or CASB telemetry can only see traffic that crosses managed network infrastructure. That leaves three structural gaps that matter most in practice:

The off-network laptop — an employee on home Wi-Fi or a personal hotspot generates no proxy logs at all.
The locally-run model — an open-weight model running through Ollama on the device makes no external request to observe.
The encrypted prompt body — even when traffic is visible, TLS means the domain is known but the content pasted into the prompt is not.

What a complete AI inventory contains

A discovery result is only useful if it supports a decision. KavachLab produces an inventory that answers the questions a security leader is actually asked in a board review:

Which AI applications, models, and extensions are in use, and by how many people.
Which of those are sanctioned, tolerated, or unknown.
What categories of data are flowing into each — PII, source code, financial, health.
Which interactions carry the highest risk score, and the factors driving it.
How exposure is trending over time, by business unit.

Start in monitor-only mode

Discovery does not require enforcement. A scoped pilot deploys the data plane into your own tenant and runs in monitor-only mode, producing a live inventory without changing anything for end users. Teams typically use that baseline to size the problem, then author policy against real observed traffic rather than assumptions.

FAQ

Shadow AI Discovery: questions we get asked

Straight answers to what security, privacy, and compliance teams ask us first.

How is Shadow AI discovery different from CASB discovery?

CASB discovery enumerates sanctioned and unsanctioned SaaS applications from network and API telemetry. It cannot see locally-run models, off-network devices, or the content of an AI prompt. Shadow AI discovery adds endpoint and browser vantage points, which is where the majority of unsanctioned AI usage actually happens.

Can KavachLab discover AI usage on unmanaged or BYOD devices?

Coverage on a device requires either the endpoint agent or the browser extension to be present. For genuinely unmanaged devices, network and cloud vantage points still provide visibility into any AI usage that crosses managed infrastructure or authenticates against corporate identity, though prompt-level fidelity requires the browser extension.

How long before we see a usable inventory?

A monitor-only pilot typically produces a live, attributed AI usage inventory within days of deploying the data plane into your tenant.

Keep reading

Ready to see every AI interaction?

Talk to our team for a guided demo and a scoped, monitor-only discovery pilot.