m1nd Neuro-Symbolic Connectome

Example Use Cases

• 1

  Efficient, token-free codebase navigation and bug detection.

• 2

  Simulate code changes and understand their impact before applying edits.

• 3

  A neuro-symbolic, evolving graph model to improve code intelligence over time.

Description

m1nd replaces traditional text search and file reads with a living graph model of your codebase, using physics and epidemiology-inspired simulations to detect bugs and structural issues that LLMs and grep cannot find. It offers sub-millisecond graph traversal, Hebbian plasticity to learn from feedback, and post-write verification to ensure code integrity. This results in 84% fewer tokens consumed, faster queries, and detection of invisible bugs through causal and structural analysis.