01

Training & evaluation data

Production-grade datasets that compile. Every sample is formally verified, human-reviewed, and ready for model training. No cleaning required.

Step 01

Identify dataset

Source from academic research, open repositories, and proprietary corpora.

Step 02

Autoformalize

Translate natural language proofs into Lean 4, Coq, or Isabelle.

Step 03

Human expert review

Domain experts verify correctness, completeness, and proof validity.

02

RL environment

Reinforcement learning environments with native proof assistant bindings. Train agents to construct and verify formal proofs with real-time compiler feedback.

environment.lean
-- Agent interacts with Lean compiler
def verify_proof (stmt : String) 
  (proof : String) : IO Bool := do
  let env ← Lean.importModules 
    [{module := `Init}] {}
  let result ← checkProof env stmt proof
  return result.isOk
03

Sample datasets

Math

Butson-Hadamard Matrices

Problem statements & solutions written in Lean, drawn from academic research. Formally verified and ready for training.

View on GitHub
Code

Programming Languages

Custom Lean datasets translated on top of the world's leading programming languages, including Python, C++ & Java.

PythonC++JavaLean 4

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