NeuroSymbolic-IR
What it is
A deterministic Intermediate Representation (IR) and graph reasoning layer that converts natural language into a typed, multi-relational semantic graph. It uses explicit opcodes (e.g., ISA, CAUSE, GOAL) to bridge LLM generation with structured reasoning, enabling constraint validation and evidence-based fact persistence.
The problem it solves
The lack of structured, verifiable reasoning in LLM outputs, which leads to hallucinations and inconsistent state management in complex agentic workflows.
What you could use it for
- Building agents with deterministic reasoning and verifiable fact memory
- Implementing complex constraint validation in AI design systems
- Providing structured interpretation and evidence-first verification for LLM outputs
- Creating long-term memory systems that require contradiction checks and backward verification
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