Lattica announced its emergence from stealth mode and raised $3.25 million in seed funding to bring fully homomorphic encryption (FHE) to cloud-based artificial intelligence applications.
The funding round is led by Cyber Fund, an investment company of managing partner Konstantin Lomashuk, and will feature additional participation from Angel Investor Sandeep Nailwal, co-founder of Polygon Network and Pentient: The Open AGI Foundation.
Lattica’s technology is intended to address persistent privacy and security challenges in sectors such as healthcare, finance and government. There, organizations are hesitant to adopt AI for concerns about sensitive data exposure. Looking at Cisco 2025 AI Briefing: CEO Edition, the company emphasizes that 70% of CEOs surveyed are concerned about network security due to increased use of AI, and 34% consider security to be a major obstacle to AI adoption.
FHE, which allows encrypted data to be queried by AI models without decryption, has long been considered a desirable goal in encryption, but has suffered from computational inefficiency up until now. Lattica claims that it was able to operate FHE by leveraging the latest advancements in the AI acceleration stack and by utilizing acceleration technologies that improve the commercial viability of FHE.
Dr. Rotem Tsabary, founder and CEO of Lattica, holds a PhD in Lattice-based Cryptography from the Weizmann Institute of Science, and will lead a team focused on the mathematical similarities between FHE and machine learning to build a cloud-based hardware presence platform for private AI computation.
At the heart of Lattica’s solution is the Homologous Cryptographic Abstract Layer (HEAL), a cloud-based service designed to improve FHE performance and streamline adoption. HEAL acts as an interface to connect FHE-equipped applications with GPUs, TPUs, CPUs and various computing hardware including dedicated accelerators such as ASICs and FPGAs.
“We have realized that by combining advances in hardware acceleration with software-based optimization, we can not only improve fHE efficiency towards commercial viability, but also solve the critical data dilemmas that hinder AI adoption in sensitive industries. “We are enabling practical FHE by developing solutions designed for neural networks.”
In connection with its debut, Lattica posted a demonstration version of its platform and shared the results of a detailed survey conducted within the FHE community. These findings suggest that 71% of participants believe that adoption is likely to rely on a hybrid approach consisting of both hardware and software innovation.
“Lattica is pushing the boundaries of fully homomorphic encryption and solving one of the most important challenges in AI security. Cyber Fund is proud to lead the previous round of Latica,” said Konstantin Lomashuk, managing partner of Cyber Fund.
The healthcare and financial industry is a specific goal for Lattica given the demand for secure, cloud-based AI applications that can process medical data without exposing such information to providers and third-party platforms. The company is looking at use cases in secure data analysis for encrypted financial transactions and medical research.
Sandeep Nailwal, co-founder of polygon networks and investor at Lattica, said, “Lattica’s product-first approach fundamentally transforms sensitive data processing in the AI ecosystem. Lattica has become a practical, scalable, practical, practical as Tsabary and her research team prove that it is important for Machine Learning Stack to drive FHE performance.
