
Autonomous Multi-Agent AI System
Situation: Complex IT and automation projects often struggle with isolated AI models that lose context, repeat errors, or lack independent quality checks and long-term memory.
Solution: Development of a structured multi-agent system built on modular Markdown files (.md) and intelligent Obsidian Vault linking. Role-based division of labor featuring central routing (Chakotay), implementation (VibeCoding), independent QA (Tuvok-QS), and client communication (EMH) with persistent memory functions.
Outcome: Reliable, self-correcting automation workflows with built-in quality gates, zero context drift, and jargon-free status reports for non-technical stakeholders.
Status: Active Core Framework (In-house Development)



