Build a KYC Agent with LangChain + Kyonis in 50 Lines of Python

Banks spend $270B/year on compliance. 95%+ of sanctions screening results are false positives. And most compliance APIs aren't designed for AI agents. We built Kyonis to fix this — an agent-native KYC/AML API with sanctions screening in <500ms, full explainability, and a free tier. Here's how to build a compliance agent in 50 lines of Python. Install pip install kyonis langchain-anthropic Get your free API key (500 verifications/month): app.kyonis.com/register The Agent from langchain_anthropic import ChatAnthropic from kyonis.langchain_tool import get_kyonis_tools from langchain.agents import initialize_agent, AgentType llm = ChatAnthropic(model="claude-sonnet-4-20250514") tools = get_kyonis_tools(api_key="sk_sandbox_...") agent = initialize_agent(tools, llm, agent=AgentType.OPENAI_FUNCTIONS) result = agent.run( "Screen these people against sanctions lists: " "1. Jean Dupont (France) " "2. Mohammed Al-Rashid (Iraq) " "Give me the risk level for each." ) print(result) What Happens Unde