Lattica, Inc. is a fast-growing R&D startup that recently emerged from stealth mode. They realized, developed, and launched their Fully Homomorphic Encryption (FHE) solution as a cloud-based service. This innovative platform enables secure querying of artificial intelligence models using FHE, bringing enhanced privacy and security to encrypted data processing without decrypting AI models. Lattica’s solution is wholly hardware-agnostic and developed exclusively for neural networks. Perhaps most importantly, it addresses bipartisan fears about network security and user privacy amid the rapid acceleration of AI technology. The company shared this exciting milestone through a press release on the morning of April 23.

Lattica is founded and run by Dr. Rotem Tsabary, its chief executive officer. He received his PhD in lattice-based cryptography from the Weizmann Institute of Science. The venture-backed platform has continued to build that impressive support. Prominent supporters include Konstantin Lomashuk’s Cyber Fund and Sandeep Nailwal, co-founder of Polygon Network.

Lattica’s cloud-based solution is taking FHE from experimental to practical and scalable, responding to a profound need across the AI landscape. Recent surveys indicate that approximately 70% of company executives view AI adoption as a key concern regarding network security and user privacy. Lattica’s technology provides a unique opportunity to address these concerns by enabling computations against encrypted data.

"Lattica’s product-first approach fundamentally transforms sensitive data processing in the AI ecosystem. Lattica has made FHE a reality that is both practical and scalable." - Sandeep Nailwal

Lattica’s mission is to make practical FHE a reality starting with a purpose-built solution for neural networks. Through patented optimization of hardware acceleration and software, Lattica makes FHE more efficient enough that it can be commercially viable.

"By combining the advancements of hardware acceleration with software-based optimization, we realized that not only could we improve FHE efficiency to the point of commercial viability, but use it to solve critical data dilemmas holding back AI’s adoption in sensitive industries. We’re enabling practical FHE by developing a solution that is tailor made for neural networks." - Dr. Rotem Tsabary