What is zkml and why is it important? | By immanuel juliet | Coinmonks | July 2025

Here is a simplified flow.

1. Train the model

import torch
model = torch.nn.Linear(2, 1)  # simple linear model

2. Compile the model in a proven circuit
Using a Giza or other compiler, converts the model to Cairo (or ZK -friendly format).

giza compile model.onnx --output model.cairo

3. Create execution reasoning + proof

giza prove --input input.json --model model.cairo --output proof.json

4. Confirmation of evidence (Onchain)

@external
fn verify_prediction(proof: Proof) -> bool 
assert(is_valid_proof(proof));
return true;

Health care: Personal diagnosis verification

financial resources: Validable credit score

gambling: AI logic for enemies without deception

Identity: Personal or repeated proof

Oracle: Onchain Defi platform using ML signal

This is not approval. This is part of what I explored while learning.

Journalist

• Compile the pytorch model with Cairo
• Check the ML output in Starknet

ezkl

• The onnx model uses Halo2 -based proof

Modular Lab

• Research -oriented ZKML tooling