Most LLM applications treat the model as the decision authority.
But in high-stakes domains (healthcare, finance, ops), that's a reliability problem.

This talk walks through TraceMind, a multi-agent Neurosymbolic architecture designed for pediatric triage guidance.

It combines:
- Multi-agent orchestration (LangGraph)
- Symbolic reasoning layer (Datalog + deterministic rules)
- Retrieval-augmented generation for grounding
- Explicit safety guardrails that override model output

Key insights:
- Why you need separation of concerns (decision logic vs. reasoning),
- How RAG grounds reliability, and why explicit orchestration beats emergent behavior.
- The pattern scales beyond Healthcare, Finance, Legal, any regulated domain.
We'll show code, architecture decisions, and lessons learned shipping this system.