Zelta
Keep your AI agents safe, controlled, and audit-ready
Zelta flips it: Propose the action → score the risk → get human approval → bind it to a one-time token → only then execute.
No more guessing what your agent actually did.
giving them tools and only checking after the damage is done.
Zelta flips it. Approval happens before execution. Token is consumed on verify. Replay and tampering get rejected.
Hey 👋
I just launched my first version of Zelta.
It helps monitor and control AI agents.
I know it's not perfect — so I’d really appreciate honest feedback.
What’s confusing?
What would stop you from signing up?
Hey everyone 👋
Curious how people are handling risky AI outputs in production?
Things like:
• Wrong actions
• Unexpected responses
• Lack of visibility
I’m building Zelta to help with this (monitoring + approvals + audit logs)
But I’d love to know — how are YOU solving this today?
Hey everyone 👋
I’m building Zelta — a tool to help teams monitor and control AI agents in production.
You can:
• Detect risky AI actions
• Add approval workflows
• Track full audit logs
I’d love honest feedback 🙏
What would you improve?
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1
The interesting challenge with AI agents is moving from letting them act to knowing when their actions need oversight.
Audit logs and approvals solve part of the problem, but the hard question is deciding which actions actually deserve a human checkpoint.
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1
That’s a great point 👀
I’ve been thinking about the same problem — audit logs and approvals are straightforward, but deciding when to require oversight is much harder.
In Zelta I’m experimenting with things like action-based rules and risk scoring, but it’s still evolving.
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1
This is interesting — I’m building something similar for AI monitoring.
Curious: how are you handling risky outputs?
(Also would love your feedback on what I’m building)
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