Before / after

The same workflow.
Now you can see it, govern it,
and prove it.

Watch one ordinary moment — a developer pasting sensitive context into an AI tool — go from something you can't see to something you can see, govern, and prove. The developer barely notices. Five short beats, start to finish.

See a risky moment governed —
in 90 seconds.

A customer record pasted into an AI tool, before and after Tether. If you'd rather poke at it yourself, the interactive version is right below.

[ 90-second walkthrough — coming ]
Before / after: a customer record headed for an AI tool
Beat 01 · before

The work happening today — invisible to you.

A developer asks an AI tool to help refactor some code, and pastes in a real customer record for context. It's a normal Tuesday. The prompt leaves the laptop and reaches the vendor. Nothing in your stack recorded what was in it, who sent it, or that it happened at all.

Without Tether — the blind spot
Action
A developer pastes a customer record into an AI prompt for context.
What left
A real customer record — names, account details — bound for an AI vendor.
Who saw it
No one on your side. EDR saw a connection; CASB saw an approved host; DLP never fired.
Your record
None. The only log of this is at the vendor — not on your timeline.
Beat 02 · after

Now you can see it.

With Tether in place, the same moment surfaces in your security view and streams to the SIEM you already run — attributed to a person, an agent, and a host. The blind spot is a channel you can finally watch.

With Tether — visible in your SIEM
Who
alex@acme, via a coding agent, from a managed laptop.
What
An AI prompt carrying content that looks like a customer record.
Where
In the security view, and streaming to your SIEM — inside your own tenant.
Tagged
The policy version in force, so the record is self-describing later.
Beat 03 · after

Policy catches the risky moment.
No ticket. No slowdown.

A pattern you named — a live credential, a customer-ID format — is stopped at the source, deterministically. Or, for a genuinely ambiguous case, the action pauses for a human instead of failing or filing a ticket. Either way, safe work around it keeps moving untouched.

The moment, governed
Trigger
The prompt matches a sensitive pattern you defined.
Named risk
Blocked at the source — no model, no waiting, with a clear reason for the developer.
Ambiguous
Paused for approval — the action waits in place rather than failing.
Everything else
Passes untouched. Safe work is never ticketed.
Beat 04 · after

An operator decides in seconds.

The paused request lands in the operator's queue with everything needed to judge it — who, what, and the policy it matched. One click. The developer's action unblocks the moment the operator approves. It's the simplest part of the whole product: a person making a fast, informed call.

operator console · approvals acme tenant live operator@acme
Time
Who · what · agent
Context
Decision
09:15:04
alex@acme  customer record  claude-code
Looks like a real customer record · managed laptop
ApproveDeny
09:11:22
kira@acme  large download  cursor
eval dataset · 14.2 MB
ApproveDeny
09:08:01
maya@acme  external link  cli
paste to a public gist
ApproveDeny
Beat 05 · after

Audit-ready evidence, produced automatically.

The whole sequence — what was about to leave, what happened, who decided — becomes a record tied to the exact policy that governed it. When an auditor asks, you hand them a signed receipt they verify offline, without taking your word for it. And it never left your cloud.

The receipt your auditor pulls
Was about to leave
A customer record, headed for an AI tool.
What happened
Caught and recorded — or approved with a name attached. Either way, on the record.
Proof
A signed receipt tied to the policy version that decided it.
Verification
Your auditor confirms it offline — no need to trust Tether.
Residency
And it never left your cloud.
Retention
Durable per-request evidence depends on your SIEM forwarding — in-memory events don't survive an Overwatch restart, which is why the SIEM adapters ship in the same release.

Run a risky moment yourself.

Pick what a developer is about to do, pick how you'd govern it, and watch the outcome — framed the way your security team would see it: what was at risk, what happened, and the evidence left behind.

What the developer does
What happens
A risky moment
Ready
Pick a scenario and a way to govern it, then run.
Ready
How you govern it

Want the raw proxy decisions and the enforcement tiers behind this? Read the technical brief →

See these five beats on your own data.

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