Nyraxis AI

CrewAI

Govern multi-agent CrewAI workflows with Nyraxis.

CrewAI Integration

Setup

import nyraxis_sdk
from crewai import Agent, Task, Crew

nyraxis_sdk.init(
    api_key="nyx_...",
    enforce=True,
    instrument=True,
    agent_name="crewai-research-crew",
)

Example crew

researcher = Agent(
    role="Research Analyst",
    goal="Find accurate information about the given topic",
    backstory="You are an expert researcher.",
    llm="gpt-4o",
)

writer = Agent(
    role="Content Writer",
    goal="Write a clear summary based on research",
    backstory="You are a skilled technical writer.",
    llm="gpt-4o",
)

research_task = Task(
    description="Research {topic}",
    agent=researcher,
    expected_output="Detailed research notes",
)

write_task = Task(
    description="Write a summary based on the research",
    agent=writer,
    expected_output="A 500-word summary",
)

crew = Crew(
    agents=[researcher, writer],
    tasks=[research_task, write_task],
)

# Every LLM call by every agent is evaluated by Nyraxis
result = crew.kickoff(inputs={"topic": "AI safety regulations 2025"})

What gets protected

  • All LLM calls from all agents in the crew
  • Tool calls and their outputs
  • Inter-agent communication
  • Final crew output

Per-agent policies

Assign different policies to different agents using agent names:

# In the Nyraxis dashboard, create policies scoped to specific agents
# e.g., "Block PII" only for the customer-facing agent

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