Runta
Gives an AI agent its own computer, with sandboxing, spend caps and an audit log around it.
Highlights
- An isolated, stateful operating-system environment per agent
- Real-time policy enforcement over OS, network, file-system, and credential access
- Per-agent spending caps to prevent runaway token and compute costs
- A full audit log of every action an agent takes
- Credential brokering so agents never handle raw secrets
- Network egress controls with allow-listed access
- Local or cloud execution with a developer SDK
- Built for production agents that execute code, touch credentials, or make external calls
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About Runta
What it is
Runta is an execution layer for AI agents: instead of adding security to a generic sandbox, it provides a controlled operating-system environment in which an autonomous agent runs with a stateful machine of its own, locally or in the cloud. It governs what the agent can reach, caps what it can spend, and logs what it did.
Why it's different
This addresses the problem everyone building agents hits second, after getting one to work at all: an agent that can run code and reach the internet is, functionally, an unsupervised process with your credentials. Most teams improvise containers around that. Building the isolation, the access controls, the spend limits and the audit trail as the substrate rather than as wrappers is the right shape, and spend caps in particular reflect real experience — a looping agent burning API credit overnight is a common and expensive failure. The caveats: it is early, it adds a dependency at the most sensitive layer of your system, and no sandbox removes the need to think about what the agent is permitted to touch.
How people use it
It is used by teams running agents that execute code or act on external systems, where the cost of a mistake is more than a bad answer. The audit log is what makes an agent defensible to a security review, since being able to say exactly what it did is usually the question. Sensible practice is starting with the tightest permissions that let the agent work and widening only where it demonstrably needs more.
Written by the n3os team. We are not affiliated with Runta.
This listing was written from public information, without Runta’s involvement. If you own it and something here is wrong — or you would rather not be listed at all — email us and we will correct or remove it.
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