Open infrastructure for AI-native software and correctness-first AI systems.

akkom-ai is a technical foundation for building LLM-driven systems that can reason, propose code changes, run tools, and operate inside real software projects — under explicit human-defined control, approval, and audit.

We focus on the missing layer between models and reality: orchestration, memory, patching, validation, execution, and traceability.

akkom-ai prioritizes correctness, auditability, and reversibility over speed or unrestricted autonomy.

Projects under akkom-ai are designed to work together as a coherent stack:

This is infrastructure for:

• AI software engineers
• autonomous agents
• game AI
• build bots
• research systems
• and anything that needs models that act, not just talk

The core runtime for AI-driven workflows.

It handles:

• runs
• context
• patch application
• tool execution
• validation
• audit trails

This is the “engine room” of akkom-ai.

A safety layer for AI-driven code modification.

It provides:

• snapshots
• diffs
• rollback
• history
• controlled patch application

Designed so that models can change code without destroying it.

akkom-ai follows three rules:

1. Models must be observable Every action must be logged, inspectable, and reversible.

2. Patches must be safe No blind writes. Everything is diffed, validated, and merge-aware.

3. Agents must be grounded Real files, real repos, real tools, real tests — no hallucinated state.

akkom-ai is not:

• a chatbot
• a prompt library
• a thin wrapper around an API

It is the substrate on which real autonomous systems can be built.

This organization is under active development. Early repositories are experimental but moving fast toward a cohesive stack.

If you are building:

• autonomous coding agents
• game AI
• research agents
• or LLM-powered infrastructure

you are in the right place.