EvoMind is a governed cognitive architecture and research platform for autonomous reasoning, memory, planning, learning, and desktop-agent execution. The architecture is organized around a closed-loop cognitive cycle consisting of perception, world-model maintenance, memory formation and retrieval, decision support, planning, governance enforcement, execution through the Raziel control layer, observation, and learning or adaptation. A primary design goal of EvoMind is the separation of cognition from language generation. The architecture emphasizes governance, auditability, provenance, reversibility, and bounded autonomy through explicit approval boundaries, policy enforcement, claim-boundary controls, and validation workflows. This release contains architecture documentation, governance documentation, validation methodology, benchmark-readiness mapping, citation metadata, public-safe diagrams, a technical whitepaper, and supporting publication artifacts. The package is intended as a research artifact and architectural reference rather than a claim of achieved artificial general intelligence. The included documentation explicitly distinguishes implemented capabilities, experimental subsystems, future-work areas, and unverified claims. Future releases will focus on external evaluation, reproducibility artifacts, benchmark evidence, and expanded deployment documentation.
Gabriel Allit (2026) studied this question.