Turn Raw Text Into Logical Structures You Can Actually Use
The missing link between AI's messy embeddings and the clean logical structures your code needs
The Problem
Current AI produces continuous, opaque neural embeddings that are powerful but impossible to integrate with logical systems. Developers are stuck choosing between AI's flexibility and logic's precision—never getting both.
The Solution
Parsimony bridges the gap between continuous neural embeddings and discrete logical structures. Like the Langlands program in mathematics, we unite two seemingly incompatible universes—but for AI.
Why Parsimony
Structure Really Does Win
Where raw embeddings are mechanistic and brutish, structured representations are elegant and simple.
Make AI outputs usable in logical systems, databases, and traditional software.
Decades of Research, Minutes to Implement
Built on patents and a century of machine learning and linguistics research.
Access cutting-edge computational linguistics without needing a PhD.
From Academia to Production
Created by academics and practitioners who've been solving real-world AI problems for decades.
Theory that actually works in practice.
Learn More
Deep dives into the technology and thinking behind Parsimony
Featured In
CEO Graham Morehead sharing insights on AI and cognition