The policy engine for agent actions
FriskAI monitors tool calls made by LLM agents and evaluates them against deterministic policies before any action runs. It gives teams a structured way to understand and control how agents interact with real systems, without changing how they build their agents today.
Core Capabilities
Everything you need to govern agents at scale. From policy modeling to deep observability.
Drop in the FriskAI SDK and get real-time visibility, enforcement, and auditability across every agent action.
- TypeScript & Python SDKs
- Framework adapters
- Sub-ms latency
from friskai import FriskClient
from friskai.adapters.langgraph import FriskLangGraphHandler
from my_agent.graph import graph
frisk = FriskClient(
api_key='FRISK_API_KEY',
)
# install once
app = FriskLangGraphHandler(graph, frisk)Express complex business rules simply.
- Visual policy builder
- JSON export
- Version history
{
"enforce": [
{
"if": "amount > 10000",
"then": [
"block",
{ "notify": "slack://risk-team" }
]
}
]
}See exactly when your agents made a tool call along with the full trace of what happened before and after.
- Complete traces of every agent action
- Full context around each tool call
- Step-by-step history before and after execution
Enterprise Readiness
Built for scale, security, and compliance from day one.
See the platform in action
Instrument a sandbox agent, review policy templates, and walk through a live incident with our team.