Runtime safety for AI agents
See the consequence before the action.
Your AI agents can delete, deploy and change things in production. Rabit checks each of those actions before it runs, forecasts what will happen in your systems, and flags it for a person when the answer is risky.
The problem
Permission isn't safety. Once it's done, it's done.
Teams give agents access so they can do real work: rotate a secret, clean up a database, ship a fix. Access answers one question, may this agent do it? It never answers the one that matters, what happens if it does? An agent can be fully authorized and still delete the wrong thing at the wrong moment, because it was wrong, or because something it read told it to.
of organizations confirmed or suspected an AI agent took an unintended or unauthorized action in the past year
Salt Security, State of Agentic AI and API Security, 2H 2026an AI coding agent on Replit deleted a company's live production database after being told not to change code
OECD AI Incidents MonitorWhat teams use today
Guardrails and filters catch what they have seen before. A new mistake looks normal.
The model checking itself is the same model that made the plan. It describes its intent; it doesn't predict the result.
Logs and monitoring tell you what happened. By then the database is gone.
Every one of these checks what an action looks like. None checks what it will do.
How it works
We check what an action will do, not what it looks like.
Rabit sits between your agent and the tools it uses. Before a write runs, three things happen:
- 01
Your agent asks first.
One call from your agent (our SDK or a plain API call) sends Rabit the action it is about to take, for example "delete the secret PROD_DB_URL".
- 02
Rabit looks at your real setup and forecasts the result.
It reads what exists and what depends on what, through read-only access. Then it forecasts what changes: what gets deleted, what breaks downstream, and whether it can be undone.
- 03
Rabit decides, and tells the agent why.
A risky action is flagged for a person, with the forecast attached, or answered BLOCK with the reason. The agent gets the reason back, so it can change its plan.
The same DELETE can be routine in one company and a disaster in another. Rules can't tell them apart. A forecast of your system can.
What you see
A clear answer for every action, and proof of it.
Review or block, never a silent pass.
Every action that reaches Rabit gets one of two answers: REVIEW, meaning a person should decide with the forecast in front of them, or BLOCK, with the reason. When Rabit isn't sure, it answers REVIEW.
A signed receipt for every decision.
Each answer is signed with a key held in AWS KMS, so you can show an auditor, a customer or your own team exactly what was decided, when, and why. You can check a receipt yourself; you don't have to take our word for it.
Who it's for
Built for the team that gets paged when an agent gets it wrong.
Platform and DevOps teams letting agents touch AWS or GitHub: secrets, workflows, deploys.You want the speed without the 2 a.m. rollback.
Companies building agents for their customers.Your customers ask what stops your agent from breaking their systems. Rabit gives you an answer, and a receipt for each decision.
Security and engineering leads who have to sign off on agent access.You get a record of what agents tried to do, and why Rabit answered REVIEW or BLOCK for each one.
Today Rabit covers agents that act on GitHub and AWS Secrets Manager. If your agents act somewhere else, tell us on the call. That's how we choose what comes next.
The pilot
Start in shadow mode. Nothing in your production changes.
- 01
A 30-minute call.
You show us the agent and the actions that worry you. We tell you honestly whether Rabit fits.
- 02
A light install.
One package in your agent, wrapped around its write tools, plus read-only access we set up with you. For AWS it can list and describe your secrets, and it can never read a secret's value.
- 03
Shadow mode.
Your agent keeps working as it does today. Rabit forecasts and decides on every write before it runs, then lets it through, and you see what each action would have caused, with a verdict and a receipt.
- 04
Week one, a real list.
What your agents were about to do, which actions Rabit would have stopped, and why. Something you can forward to your manager.
Shadow mode is free while we set it up together. If it earns its place, the pilot is a flat monthly fee: no per-seat counting, no long contract.
Book a callStraight talk
Where we are, honestly.
What Rabit does today
Checks an agent's write actions before they run, on GitHub and AWS Secrets Manager
Forecasts the result from read-only access to your setup
Flags a risky action for a person, with the forecast, or answers BLOCK with the reason
Signs a receipt for every decision with a key in AWS KMS
What it doesn't do yet
Approve actions on its own. In the pilot every answer is REVIEW or BLOCK
Promise it is always right. A forecast can be wrong, which is why risky actions are flagged for a person
Give you an accuracy number. We haven't measured one yet, and we'll measure it with you before we print one
Cover every system. AWS and GitHub first, then what our pilot partners need
Rabit is founder-led and taking a few pilot partners, so you work with the founder directly. If that suits you, let's talk.
Adam Shibli, founder · LinkedInFAQ
Between your agent and the tools it uses. You can add it through our SDK or with one API call. An MCP server, or a gateway for agents on a hosted platform, is built with the pilot partner who needs one.
The nest
Show us the action that keeps you up at night.
Thirty minutes, with the founder. Bring one agent and the one thing you'd never want it to do on its own. We'll show you what Rabit would have said, and tell you straight if it isn't a fit.
Book a callRather write? adam.shibli2001@gmail.com