A Modern, Scalable Architecture for Complex Simulations.

Our framework is built on a foundation of modern, proven technologies, designed for scalability, extensibility, and deployment in the cloud.

MonkeyMinds System Architecture Diagram

Our Guiding Principles.

Modular & Service-Oriented

The framework is composed of independent, loosely-coupled services. This makes the system easier to develop, test, and maintain, and allows for independent scaling of its components.

Asynchronous & Event-Driven

We use an asynchronous, event-driven architecture to handle the complexity of multi-agent simulations. This allows for high performance and scalability, even with a large number of concurrent personas.

Extensible & Customizable

We have designed the framework to be easily extensible. New models, behaviors, and even entire new modules can be added with minimal friction.

Our Technology Stack.

Python Logo

Core Logic: Python

The core simulation engine and persona generation logic are written in Python.

Node.js Logo

Web & API Layers: Node.js

Our web applications and APIs are built on Node.js.

React Logo

Frontend: React

The user-facing web applications are built with React.

MongoDB Logo

Database: MongoDB

We use MongoDB as our primary data store.

Built on a Foundation of Open Source.

We believe in the power of open source. Our framework is built on a foundation of best-in-class open source technologies. We are committed to contributing back to the community as we grow.

Responsible AI & Privacy.

Data Approach

  • Simulation-first. We use synthetic personas and environments by default.
  • Customer data is optional and, when used, should be anonymized or pseudonymized.
  • No data is sold. Access is restricted to authorized processes only.

Security & Controls

  • Encryption in transit (TLS). Encryption at rest supported by managed storage.
  • Environment and API separation for web, services, and data layers.
  • Config-driven retention and deletion policies; export on request.

Model Governance

  • Transparent prompts and parameters internally; versioned runs for auditability.
  • Safety filters for generated content and guardrails for persona behaviors.
  • Human-in-the-loop review for high-impact scenarios.

Compliance Readiness

  • Designed to support privacy-by-default workflows.
  • Documentation to assist with DSRs, DPIAs, and vendor assessments.
  • Cloud-agnostic deployment patterns to match your controls.