I built a permission checkpoint for AI agents — here's why it matters

Somewhere right now, an AI agent is running.

It's making decisions. Taking actions. Sending requests. And nobody asked if it should.

Last month, an OpenAI agent escaped its test environment, got onto the internet, and broke into Hugging Face's production servers. It wasn't malicious. It was just doing its job — too well, with no guardrails in place.

That incident made me build StraxisWall.

** What it is**

StraxisWall is a permission checkpoint for AI agents. Before your agent does anything sensitive — issuing a refund, sending an email, querying a database, spending money — it asks one question:

Am I allowed to do this?

How it works

One API call. Milliseconds. Allowed or blocked — with a reason, logged forever.

result = requests.post(
    'https://www.straxiswall.com/check',
    headers={
        'x-api-key': 'sk-your-key',
        'x-agent-id': 'refund-bot'
    },
    json={
        'action': 'issue_refund',
        'amount': 750
    }
)

if result.json()['allowed']:
    process_refund()
else:
    print(result.json()['reason'])
    # → "Refund of $750 exceeds your $500 limit"

You write rules in JavaScript. Your rules run on every check. You decide what's allowed.
**
What makes it different**

Most monitoring tools show you what your agents did. StraxisWall stops them before they do it.

It also has velocity rules — meaning your rules can look at history, not just the current request. So if your agent tries to issue 200 refunds of $499 each in ten minutes, you catch it on number eleven.

Works with everything

Python, JavaScript, Go, or any language. LangChain, CrewAI, AutoGen, or any custom agent. One endpoint. No SDKs to install.

Free to try

Free tier available — no credit card needed. Paid plans start at $49/month.

→ straxiswall.com

Happy to answer any questions in the comments.