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RiskKernel
Open-source runtime enforcing hard cost, loop, and time limits on AI agents. Self-hosted, no telemetry, LLM proposes, code disposes.
Overview
RiskKernel is an open-source, self-hosted runtime designed to put deterministic guardrails around any AI agent. It enforces per-run cost, loop, and time budgets in Go—never relying on an LLM for enforcement. By simply setting one environment variable, you can point an existing agent at RiskKernel and gain hard limits, crash-resume capabilities, human approval gates on side-effecting tools, and OpenTelemetry export. Your keys, your infrastructure, and zero telemetry leakage. Licensed under Apache-2.0, RiskKernel ensures that while the LLM proposes actions, deterministic code disposes of unsafe or runaway behavior.
Key Features
Per-run cost, loop, and time budgets enforced deterministically
Point an existing agent at RiskKernel with one environment variable
Crash-resume for interrupted agent runs
Human approval gates on side-effecting tools
OpenTelemetry export for observability
Your own keys, infrastructure, and no telemetry
Apache-2.0 open-source license
Pros & Cons
Pros
- arrow_right + Determines safety via code, not LLM
- arrow_right + Self-hosted with no telemetry or vendor lock-in
- arrow_right + Crash-resume ensures no wasted runs
- arrow_right + Human oversight on dangerous tool calls
- arrow_right + Easy integration with existing agents
- arrow_right + Open source under permissive Apache-2.0
Cons
- arrow_right - Requires self-hosting and infrastructure management
- arrow_right - Limited to agents that can be instrumented via environment variables
- arrow_right - No built-in GUI, primarily CLI/service
- arrow_right - Learning curve for custom budget configuration
Pricing Details
RiskKernel is free and open source under the Apache-2.0 license. You can self-host it on your own infrastructure with no usage fees or hidden costs. There are no premium tiers or paid features—all functionality is available in the open-source repository.
FAQ
How does RiskKernel enforce limits without relying on the LLM?
expand_moreAll budget checks are performed by a deterministic Go runtime, not by the LLM itself, ensuring that the agent cannot override or bypass limits.
Can I integrate RiskKernel with existing agents?
expand_moreYes, simply set one environment variable to redirect your agent's tool calls through RiskKernel. No code changes are required.
Is telemetry sent to any external service?
expand_moreNo. RiskKernel is self-hosted and does not collect or transmit any telemetry. You can optionally export metrics via OpenTelemetry to your own monitoring system.
What happens if an agent exceeds its budget?
expand_moreThe runtime automatically terminates the run. Thanks to crash-resume, you can restart from the last checkpoint.
Is RiskKernel suitable for production use?
expand_moreYes, it is designed for production AI agents and includes human approval gates for sensitive actions.
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Host Your SaaS on Antigravity Cloud
Fast, secure, and developer-friendly hosting for modern web applications.
Smart Alternatives & Comparison
Compare RiskKernel side-by-side with other leading tools in the same category.
| Criteria |
RiskKernel
This Tool
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| Overview | Open-source runtime enforcing hard cost, loop, and time limits on AI agents. Self-hosted, no telemetry, LLM proposes, code disposes. | Manage local and cloud AI agents from your editor. Plan, delegate, review, and ship code without context switching. | Ship API integrations instantly. Forward deploys AI agents into your customers' repos, auto-writing and testing integrations in minutes. | Spawn background coding agents in the cloud. Hand off tasks from Slack, Linear, or GitHub and get a PR back. |
| Pricing Model | Freemium | Freemium | Freemium | Freemium |
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| Developer API | cancel Not Available | cancel Not Available | cancel Not Available | cancel Not Available |
| Open Source | lock Proprietary | lock Proprietary | lock Proprietary | lock Proprietary |
| Action | Visit Web open_in_new |
