Govern every action your AI agents take.
Before the auditor asks.
AgentGovern intercepts every autonomous AI agent action at runtime, evaluates it against policies written as code, and generates audit-ready evidence, continuously.
The deadlines are real.
Three regulatory clocks are running. Each one demands continuous evidence of how your AI agents make decisions.
Article 9, 10, 13, 14
High-risk AI systems must demonstrate risk management, data governance, transparency, and human oversight. Documentation alone isn't enough. Regulators expect runtime evidence: which agent made which decision, against which policy, with what input.
SB 24-205
The first US state law requiring AI developers and deployers to use reasonable care to prevent algorithmic discrimination. Annual impact assessments. Adverse action notifications. Consumer rights to appeal AI decisions.
2026 Exam Priorities
The SEC has named AI governance as a priority for 2026 examinations of investment advisers and broker-dealers. Examiners will ask how you supervise autonomous AI systems, how you detect drift, and what your evidence trail looks like.
Compliance-as-Code, in three steps.
Three lines of Python. One YAML file. One dashboard.
Three lines of Python. No infrastructure changes.
Install the AgentGovern SDK. Wrap your existing LangChain or LangGraph agent. Every tool call, LLM completion, and decision your agent makes is now intercepted and ready for evaluation. Less than five milliseconds of overhead per action.
If AgentGovern is unreachable, the SDK fails silently and your agent continues. Governance never breaks production.
from agentgovern import govern
@govern(policy="eu-ai-act")
def credit_scoring_agent(application):
return langchain_agent.invoke(application)Policies as code, not as PDFs.
Write compliance rules as YAML files in a Git repo. Map directly to EU AI Act articles, NIST RMF controls, SEC governance requirements, or internal policies. Version control. Pull request review. CI/CD deployment. Treat compliance the way you treat infrastructure.
AgentGovern ships with policy packs for EU AI Act, NIST RMF, and ISO 42001. Customize them. Add your own. Audit-ready means audit-ready.
policy: human-oversight-flag
framework: eu-ai-act
article: 14
applies_to:
action_type: decision
risk_level: critical
rules:
- require: human_review
when: confidence < 0.85
severity: criticalContinuous evidence. Regulator-ready reports.
Every agent action is timestamped, evaluated against every applicable policy, and stored. Real-time compliance scores. Drift alerts when agents deviate from baselines. One-click audit reports for EU AI Act conformity assessments.
When the auditor asks for evidence, you don't open a spreadsheet. You generate a report.
Last Tuesday at 2:47 PM, your credit scoring agent approved a loan for an applicant in Frankfurt. Your auditor wants to know which version of which policy was applied, what input the model saw, what the confidence threshold was, whether a human reviewed it, and whether the decision aligned with EU AI Act Article 14 on human oversight.
Today, answering this question takes a project, three lawyers, and a four-week scramble.
AgentGovern answers it with a query.
Evidence, generated from code.
A new category.
AI governance platforms operate at the documentation layer. They help you write down what your AI does. They don't watch it.
GRC platforms automate evidence collection for SOC 2 and ISO 27001. They were built for infrastructure compliance, not for AI agents making thousands of autonomous decisions per hour.
AI observability platforms watch model performance. They tell you when latency is up. They don't map agent behavior to regulatory requirements.
AgentGovern operates at the runtime layer. Every autonomous agent action, evaluated in real time, against policies written as code, mapped to the regulatory frameworks that govern your industry.
That's the layer we built for. We call it Compliance-as-Code for agentic AI.
Get started
Talk to the founder.
Ahmed Khan, founder and CEO of Zirahn. Twenty minutes, your roadmap, our roadmap, no slides.