Why Kairo

Everyone tests the code. The risk is in the behavior.

A scanner reads what the code says. An attacker cares what the application lets them do.

Backed by

150+Cyber incident responses led

Engineers from

The problem

AI ships code continuously. Pentests only happen periodically.

In between: static scans, which read the code and nothing else. Everything shipped between two pentests reaches production read but never tested.

Code shipped: humans and AI agents

Continuous

Security tested: pentests and static scans

4 / year

The shift

Application testing was built for an attacker whose time was expensive. That constraint is gone.

They read everything first
Docs, changelogs, public API surface, error text. All before a single unusual request.
They chain the harmless
“Remove auth” and “make it public” are each routine in review. Together, a breach.
Being wrong is free
A human abandons a dead end in an hour. An agent abandons it in a second, so it tries what nobody thought worth trying.
They work for you, too
The agents inside your product hold tools, permissions and autonomy. Normal has to be learned before abnormal can be stopped.

The model

Predict how humans and agents will act. Simulate it against a shadow environment. Verify every change. Feed what you find back into the model.

Behavioral security model
Predicting humans and agents
Who uses the application, what they want, which automations act for them, and what each path is implicitly trusted to do.
Shadow environment
24/7 live context
A running copy with live-shaped data. Nothing touches production, and nothing stays theoretical.
Harden and verify
Verify every change
Weak spots predicted and fixed. Every change verified before it ships, every finding reproduced first.
Every finding feeds back
Closed loop
A finding strengthens the model, not just a ticket. Each release starts from a better prediction.

Every finding feeds back into the model

Ship secure

Where Kairo pulls ahead

Every finding is proved
Validated findings with the evidence attached, not a wall of scanner alerts for someone to triage.
Caught before it ships
After launch, an attacker has already had a window. The test belongs at the change, not at the quarter.
Attack surface hidden across changes
Two routine pull requests, weeks apart, that only become a breach in combination. The class of finding a per-diff reviewer cannot see.
Unpredictable agent behavior
Learn what normal looks like for the agents in and around your product, then stop what is not.
What a change will break
The shadow environment runs the change before it is real, so the answer arrives before the deploy does.