The missing cognitive primitive for AI agents. Decompose any text into classified semantic units — authority, risk, attention, entities. No LLM. Deterministic.
Non-LLM deterministic semantic decomposition—14ms, no hallucination, MCP-ready.
AI agents, contract review, legal tech, RAG pipelines, document intelligence systems
Anthropic Structured Extraction · Haystack · Unstructured.io
Deterministic graphs instead of vector embeddings sound clever, but long-context windows and RAG tools already solve this problem cheaper.
No LLMs — template matching beats stochastic bash generation for reproducibility.
Deterministic semantic engine replaces LLM hallucinations with math-derived blueprints.
Compresses 28M tokens to 100k queryable chars local-only; duplicates RAG problems at smaller scale.
Solves an unsolved problem: format incompatibility between Claude, GPT, LLaMA documented by research.
Visual chunking comparison beats guessing — export production-ready code.
