JSTprove Public Launch Brings Verifiable AI to Developers

October 31, 2025 – Inference Labs has announced the JSTprove public launch, a major step toward making Zero-Knowledge Machine Learning (zkML) accessible to developers and organizations worldwide. Built on Polyhedra Network’s Expander backend, JSTprove simplifies the generation and verification of AI inference proofs through an easy-to-use command-line interface, bridging the gap between cryptography and machine learning.

JSTprove Public Launch Redefines zkML Accessibility

The JSTprove public launch introduces a full end-to-end pipeline for zero-knowledge AI proofs. It accepts ONNX models and automates proof generation and verification through Polyhedra’s Expander Compiler Collection. Users can generate circuits, witnesses, and proofs without cryptographic expertise, making verifiable AI practical for real-world applications in finance, cybersecurity, and healthcare.

The toolkit supports core CNN layers such as Conv2D, MaxPool, ReLU, and Fully Connected, and it’s fully open-source allowing developers to inspect, audit, and extend its capabilities.

Inside JSTprove: How Verifiable AI Works

At its core, JSTprove turns conventional AI inference into transparent, auditable computation. The process involves quantizing an ONNX model, generating circuits via Expander, and creating proofs that confirm the model executed as intended without exposing private parameters.

This ensures trust in AI decisions, preserving both accuracy and confidentiality. Each command outputs reproducible artifacts for traceability, making JSTprove a true bridge between AI and cryptographic proof systems.