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The MindLab platform is designed to provide a robust, scalable, and governable environment for AI-driven workflows. The architecture is built around a clear flow of information and control, ensuring that every task is executed with precision and predictability.

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The Flow of Information

The core of the MindLab architecture is a logical flow that begins with a user’s intent and ends with a verifiable outcome. This process can be broken down into the following steps:
1

Intent

The process begins when a user provides a high-level Intent to the Orchestrator. This intent is a description of the desired outcome, rather than a specific set of instructions.
2

Selection

The Orchestrator analyzes the intent, consults its knowledge base, and selects the most appropriate Capsule(s) from the marketplace to fulfill the request.
3

Planning

The Orchestrator reads the CADANCE™ Spec (the manifest) of the selected Capsule to understand its capabilities, constraints, and workflow structure. It then generates a specific, executable plan (a DAG) based on the user’s intent and the Capsule’s playbook.
4

Execution

This plan is handed off to the Flow Engine for execution. The Flow Engine calls upon the specific agents defined in the Capsule and leverages its own durability features to ensure the successful completion of the workflow.