Belfort Releases Fastest Encrypted Image Classifer

Belfort released the fastest encrypted image classifier, a ResNet-20 implementation under encryption achieving 163ms latency, outperforming prior state-of-the-art by 3x. The company's Cyclops GPU library enables this performance, marking a milestone for practical encrypted AI. Belfort is working with Google on the HEIR compiler to improve tooling.

Belfort releases fastest Encrypted Image Classifier available San Francisco / Leuven,July 16, 2026 — Belfort today released the "so far" CIFAR demo, an encrypted implementation of ResNet-20, a popular model for image classification. It outperforms recent SOTA by 3x with a total latency of less than 200ms. A public demonstration is available at sofar.belfortlabs.cloud https://sofar.belfortlabs.cloud/ . The AlexNet Moment For Encrypted AI When AlexNet was trained and run on GPUs in 2012, it proved that hardware had finally caught up to the ambition of neural networks, and that one result unlocked the decade of AI that followed. Encrypted AI is at the same inflection point. Running ResNet-20 under encryption in 163ms might be our AlexNet moment: the signal that encrypted computing has crossed from theoretically possible to practically useful, and the foothold for the larger models coming next. Try it live at sofar.belfortlabs.cloud https://sofar.belfortlabs.cloud/ . These significant speed-ups come without any impact on the accuracy of the underlying AI model, the model accuracy of 92.5% matches that of the non-encrypted model 92.8% . Machine learning engineers can now focus on accuracy and assume the performance is taken care of. Performance-Enabled Accessibility Belfort's image classification is built on top of its upcoming GPU library, Cyclops. It comes with several optimizations that make Cyclops extremely fast on Encrypted AI workloads. This performance increase translates to many other similar machine learning algorithms too. As Belfort’s CTO Michiel Van Beirendonck states: “Two years ago, running an AI model under encryption was out of reach. Cyclops closes that gap, and it's the same gap we'll keep closing as the models get bigger. This is the start of a trajectory, not the finish line.” “Two years ago, running an AI model under encryption was out of reach. — Michiel Van Beirendonck , Belfort Co-Founder & CTO Beyond performance, we are working with Google https://belfortlabs.com/blog/google-partnership on their HEIR compiler, to make encrypted computing as easy as possible. “Running encrypted AI workloads not only requires performance, but also the tooling to adapt the models and tweak the performance”, says Alexander Viand, Senior Software Engineer at Belfort. Future releases will not only bring increases in performance, but also an extended feature set to make it easy to use. What’s next and availability This Resnet-20 demo is one step in a larger effort to make encrypted AI fast enough for real use. The work behind Cyclops carries over to other models, and that's where we're headed next: bigger networks, broader model support, and better tooling to make encrypted workloads easier to run. Cyclops is currently in alpha with early partners. Organizations interested in testing encrypted AI on their own workloads can reach out for early access. About Belfort At Belfort, we believe that in an AI-first world, trust is all you need and the future of computing is encrypted. Belfort enables that vision by accelerating Encrypted Compute to make it practical at scale, ensuring that sensitive data can be processed without ever being decrypted. A spin-off from KU Leuven’s world-renowned COSIC lab, Belfort combines breakthroughs in hardware and algorithms to build the next layer of secure computing. The company has offices in San Francisco, USA, and Leuven, Belgium. https://belfortlabs.com/ https://belfortlabs.com/