Introduction

Welcome to the Mankinds documentation.

Mankinds is an agentic AI governance platform. Autonomous agents evaluate and monitor AI systems across 8 trust dimensions — privacy, security, accuracy, fairness, explainability, accountability, sustainability and systemic risk — continuously, from development to production, grounded in regulatory knowledge.

The platform combines a dual knowledge graph architecture (70+ regulatory frameworks), autonomous evaluation agents, and structured outputs (scorecards, risk sheets, audit packages) to turn compliance from a manual process into an automated, auditable one.

Key Capabilities

• Offline evaluation — Connect an AI system via API or SDK. Agents run structured test scenarios against the system using ground truth datasets.
• Online evaluation — Connect observability tools (Langfuse, LangSmith, Datadog). Agents analyze real production traces to detect drift and degradation.
• 86 evaluation criteria across 8 dimensions, grounded in EU AI Act, GDPR, ISO 42001, NIST AI RMF and 70+ regulatory frameworks.
• 30+ pre-built connectors — databases, observability platforms, document sources, and AI system endpoints.

Resources

• SDK: JavaScript/TypeScript and Python SDK documentation
• Knowledge Glossary: Key terms definitions for AI evaluation

Quick Start

Choose your language:

In a few minutes, evaluate your first AI system.

Get an API key

Create an account on app.mankinds.io and generate your API key from settings.

Install the SDK

pip install mankinds-sdk

Configure and use

from mankinds_sdk import MankindsClient

client = MankindsClient(api_key='mk_your_api_key')

# Create a system, generate a dataset, evaluate
system = client.create_system('My Chatbot', '...', endpoint={...})
dataset = client.generate_dataset(system['id'], num_scenarios=10)
result = client.evaluate(system['id'])
print(f"Score: {result['summary']['overall_score']}")

See the full SDK guide for the detailed API reference.

Support

For any questions: [email protected]