The NeuNuc agent system is not a chatbot. It is an architecture for retrieval, synthesis, execution, and audit — with humans at every gate that matters.
The central orchestrator that routes tasks to the right agents, maintains context, and enforces approval boundaries.
Semantic search across the knowledge graph. Retrieves relevant context before any decision is made.
Builds a working context window from multiple sources: documents, conversations, lore, and user memory.
Routes tasks to specialized agents with clear contracts. Each agent has a domain, a scope, and an evaluation method.
Humans retain authority over high-stakes decisions. The system asks before acting on irreversible operations.
What the system remembers, and how you can verify everything it did.
Preferences, patterns, and history persist across sessions. The system learns how you work without compromising privacy.
Organization-wide knowledge, rules, and standards. Versioned, auditable, and queryable by every agent.
Every agent output includes its sources, reasoning path, and confidence level. No black boxes.
Full audit trail of what was proposed, what was approved, and what was executed. Searchable and exportable.
How we know the agents are doing what they should.
Continuous assessment of retrieval accuracy, synthesis quality, and execution correctness against labeled benchmarks.
Not all tasks should be automated. The system identifies decisions that require human judgment and pauses for approval.
Run on local hardware for privacy-critical work. Fall back to cloud providers for capacity. Switch at runtime.