Runtime security layer that stops risky AI actions before they execute
Stage
Established
Not given
Founded
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Based in
DE
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Pricing model
Freemium
Freemium
Pricing
Not given
Free plan: Local Guard runtime with real-time approval prompts and local audit log. Solo $4.99/mo: adds 2 cloud-connected devices and 30-day cloud retention. Pro $15/mo: adds 5 cloud-connected devices, 180-day retention, and policy versioning. Team $30/seat/mo: up to 25 cloud-connected devices, 365-
Key features
Hierarchical traces capture every LLM call, tool invocation, and retrieval step
LLM-as-a-judge, heuristic functions, or human review evaluations
Prompt management with one-click deployments and rollbacks
Playground to test prompts on real production inputs and compare models
Experiments with test cases and side-by-side comparison
Human annotation and collaborative human-in-the-loop workflows
Cost and latency monitoring with dashboards and alerts
REST APIs and Query SDK for data access
Langfuse Assistant to automate the AI engineering loop
Surface-specific pre-action interception
Policy routing with allow, observe, ask, and block outcomes
Local review and evidence workflows
MCP, skill, plugin, and package inspection
Layered local and team policy
Open source runtime under Apache-2.0
Offline local protection without cloud connectivity
Continuous GitHub leaked-secret monitoring
Decision audit trail and export
Support for multiple AI coding agents
What makes it different
MIT licensed open source platform with no data lock-in
Enterprise scale architecture handling billions of monthly events
Works with any language and framework with no framework lock-in
Async by default so tracing never blocks your application
Open-source core runtime runs locally without cloud requirement
Protects against secrets, destructive commands, prompt injection, and supply chain attacks
No source code or secrets uploaded; decisions stored as redacted summaries