HashCloak's R&D project explores publicly verifiable computation over private shared state through a privacy-preserving logistic-regression training pipeline. It combines TACEO's co-noir framework and a collaborative-SNARKs backend with fixed-point arithmetic and polynomial sigmoid approximations, demonstrating simulated three-party MPC training on commodity hardware.
