Agents

Documentation status: guide — see Maturity and evidence.

logiCells provides a semantic runtime for governed agentic systems.

Rather than treating a prompt and an LLM conversation as the stable state of an agent, logiCells maintains an explicit conceptual representation of the world. Perception, reasoning, memory, action, and reflection enrich or transform that governed world model.

Fast paths

• Neuro-symbolic governance
• Knowledge engineering
• All tasks

Core idea

Conventional agent loop
  perception -> reasoning -> action -> reflection

logiCells agent runtime
  governed conceptual world model
    <- perception enriches it
    <- reflection consolidates it
    -> reasoning explores alternatives
    -> actions interact with the external world through governed interfaces

The architecture is designed to:

• represent the world before acting on it;
• enrich that representation through perception;
• explore hypotheses through isolated or layered conceptual states;
• combine symbolic, neural, and language-based reasoning;
• expose controlled actions through MCP and other governed interfaces;
• record decisions, actions, validations, and failures;
• consolidate experience into reusable memory.

Main sections

• Agentic architecture
• Layered conceptual world
• Agent memory graph
• Tri-engine reasoning
• MCP boundary
• Agent roles
• H-Logic agent model
• Semantic virtual machine

Strategic positioning

logiCells is not only a knowledge graph, an agent framework, or an ERP adaptation layer. It is a semantic runtime in which language models, graph-learning models, symbolic rules, execution mechanisms, and governed external actions operate over a shared conceptual world.