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DOC2MATH™
Document-to-Mathematics Problem Genesis Engine
Convert technical documents into formal mathematical problem structures. Extracts variables, operators, constraints, objectives, and uncertainty into Machine-Parseable Structure (MPS) JSON using the Zero-Inference Protocol — closed-world, grounded, inference-tagged.
- Stage 1 MPS JSON pipeline (variables → constraints → objectives)
- Zero-Inference Protocol: MISSING-marked, grounded, no hallucination
- Validated against OptNet and academic optimization papers
- Uncertainty and inference tracking built in
- Runs locally — your key, your data, zero vendor lock-in
- Python 3.9+ · 3 files · no external dependencies beyond anthropic SDK
Bring Your Own Key. This tool runs on your machine with your own Anthropic API key.
IntuiTek¹ never stores your key or processes your data. One-time purchase — no subscription, no lock-in.