Sigilant · Control for AI agents
AI agents are already raising orders, changing records and moving money inside your systems, on keys nobody can trace to a person. Sigilant makes every agent act as itself, with permission, with proof.
Does this sound familiar?
Each one has an honest answer today, and it is not a good one. Sigilant exists so the answer becomes a record you can show.
The purchase order (from our demo)
Today: the agent used a shared password. The finance system logged the password, not the agent. Ten agents use the same one, so nobody can say which agent did it, for whom, or whether anyone said yes.
With Sigilant: the order was over the limit, so it waited. A named manager approved that exact order, and the record shows her approval.
The audit
Today: a spreadsheet, maybe. Government security rules now expect a list of every AI agent and who is responsible for it, and regulators expect you to stand behind the work they do.
With Sigilant: every agent is on the list with a named owner, who confirms every so often that it is still needed. An agent nobody vouches for stops and waits for a person.
The rollout
Today: the safe answer is no, so the project stalls. Or it goes ahead with a password hidden inside the agent, and everyone hopes.
With Sigilant: the agent never holds a password. Sigilant lets it in for the one approved action, then closes the door. Security can say yes.
What it costs you today
Who did it, on whose behalf, and who approved it. Three questions, no reliable answer.
Turning off a shared password breaks everything that uses it. So nobody does, until it is too late.
Agents arrive inside software you buy and tools your teams build. The ones you cannot see are the ones that hurt.
Every agent the business wants is a risk you carry personally. Saying yes needs something to point to.
A real run
From our demo: a purchasing agent, a manager called Priya, and a finance system. Nothing in the agent or the system was rebuilt.
How it works
Agents go through Sigilant to reach your systems, instead of going straight in. Neither the agent nor the system behind it has to be rebuilt.
Step 01
Each action is checked against your rules before it happens: which agent, for whom, doing what.
Allow, hold or refuse
Step 02
Actions you mark as high-risk are held for a named person, who sees exactly what they are approving.
A person in the loop
Step 03
The agent never holds the keys to your systems. Access is supplied for the one action, then gone.
Nothing to steal
Step 04
Every decision, allowed or refused, is written to a record that shows if it has been altered.
Evidence as a by-product
What you can now say
Each one is a capability, written the way you will have to say it.
Find them first
AI agents arrive inside software you buy and tools your teams build, and most organisations only meet theirs during an incident. Sigilant looks first: it searches your code and your systems for AI agents, AI tools and passwords to AI services, and asks a person to claim each one or switch it off.
It keeps looking. Every change your teams make, every release and every day, it checks again, so "are we still safe?" has an answer you can show, not a feeling.
Deployment
Your people log in and approve with the login system you already use, such as Okta, Auth0 or Microsoft Entra ID, and agents belong to the teams you already have. Sigilant runs on your own systems: your rules, your records and what your agents do stay with you.
We will show you how Sigilant controls it, on your systems, with your rules. One hour, and you leave with the record.
Get in touch
Tell us which agents you are putting into production and what they need to reach. We will reply within one business day.
