Hybrid AI FAQs

Question 1

What is Hybrid AI and what problem does it solve?

Accepted Answer

Hybrid AI is an MCP server that uses transparent McCulloch-Pitts neurons to create an inspectable decision layer. It solves the 'black box' problem of complex neural networks, providing clear explanations for safety-critical and regulated AI applications.

Question 2

How does Hybrid AI make AI decisions transparent?

Accepted Answer

It acts as a 'post-NN calculator,' taking high-level outputs from opaque neural networks and applying simple, transparent logical rules via McCulloch-Pitts neurons. This allows for fully explainable and auditable final decisions.

Question 3

Which industries or applications benefit most from Hybrid AI?

Accepted Answer

Hybrid AI is ideal for safety-critical systems (e.g., self-driving cars, medical diagnosis) and regulated industries (e.g., finance, healthcare, insurance) that require explainable, auditable, and compliant AI decisions.

Question 4

Can I define my own custom decision rules with Hybrid AI?

Accepted Answer

Yes, you can create and apply named decision rules using standard logic gates (AND, OR, NOT, XOR) or custom MCP neuron configurations. These rules come with human-readable descriptions for transparent, explainable logic.

Question 5

How does Hybrid AI ensure auditability and regulatory compliance?

Accepted Answer

Hybrid AI provides comprehensive decision logging and audit trails. Every decision made is recorded with a full, step-by-step explanation of the logic, inputs, and outcome, which is crucial for regulation and accountability.

Hybrid AI

Hybrid AI

Key Features

Use Cases

Key Features

Use Cases