The Good Tech Companies - Why Lattica’s $3.25M Bet on Fully Homomorphic Encryption Could Change AI Privacy Forever

Episode Date: April 23, 2025

This story was originally published on HackerNoon at: https://hackernoon.com/why-latticas-$325m-bet-on-fully-homomorphic-encryption-could-change-ai-privacy-forever. Lattica raises $3.25M to make Fully Homomorphic Encryption viable for AI, tackling privacy risks in sensitive industries like healthcare and finance. Check more stories related to tech-stories at: https://hackernoon.com/c/tech-stories. You can also check exclusive content about #lattica, #good-company, #funding, #ai, #cryptocurrency, #ai-ml, #lattica-news, #data, and more. This story was written by: @ishanpandey. Learn more about this writer by checking @ishanpandey's about page, and for more stories, please visit hackernoon.com. Lattica raises $3.25M to make Fully Homomorphic Encryption viable for AI, tackling privacy risks in sensitive industries like healthcare and finance.

This audio is presented by Hacker Noon, where anyone can learn anything about any technology. Why Latica's $3.25 million bet on fully homomorphic encryption could change AI privacy forever. By Aishan Pandey. Hash hash how can AI stay private? Latica's $3.25 million funding pushes fully homomorphic encryption into the spotlight can AI process sensitive data without ever exposing it? This is the question Tel Aviv based startup Latika is attempting to answer as it steps out of stealth mode with $3.25 million in pre-seed funding. The company's mission, solve one of artificial intelligence's most persistent privacy challenges using fully

homomorphic encryption, FHE, breaking down Latika's funding and investor interest. encryption, FHE, breaking down Latika's funding and investor interest. Latika's pre-seed funding, led by Konstantin Lomashuk's Cyber Fund, includes participation from notable investors like Sandeep Nailwal, co-founder of Polygon Network and Censhunt, the Open AGI Foundation. The $3.25 million pre-seed injection positions Latika to scale its cloud-based platform, which promises secure AI computation by enabling queries over encrypted data, without ever decrypting it. Investor interest signals a rising demand for privacy-enhancing technologies ENI, particularly

in industries where compliance with data protection regulation is non-negotiable. According to Cisco's 2025 AI briefing, security remains a top concern, with 34% of CEOs citing it as a barrier to wider AI adoption. What makes Latica's approach different? FHE has long been hailed as the ''holy grail'' of cryptography, offering a way to compute on encrypted data. Yet, due to performance inefficiencies, it has largely remained a theoretical solution. Latica addresses this challenge through its homomorphic encryption abstraction layer, HEAL, which standardizes and accelerates FHE operations across various hardware environments, including GPUs, TPUs, and ASICs, Dr. Rodham Sabary, founder and CEO, explained,

greater than, we're enabling practical FHE by developing a solution that is tailor-made for greater than neural networks. With a background in lattice-based cryptography from the Weizmann Institute, Sabari's vision leverages both hardware and software optimization to bridge the gap between secure computation and scalable AI deployment. Industry Focus Healthcare and finance in the crosshairairs Latika's platform is especially relevant to sectors like healthcare and finance, where sensitive data handling is both a regulatory

and operational concern. Applications range from encrypted financial transactions to secure analysis of medical data for research purposes," Sandeep Nailwal commented. Greater than, Latika's product first approach fundamentally transforms sensitive data greater than processing in the AI ecosystem. Advances in the machine learning stack are greater than significantly boosting FHE performance. The startup's own survey within the FHE community revealed that 71% believe FHE adoption will depend on combining hardware and software, validating Latica's hybrid approach. Market implications and final thoughts Latica's emergence reflects a broader trend, the increasing pressure

on AI providers to ensure data privacy at all costs. As regulatory environments tighten globally, and as AI becomes further embedded in critical infrastructure, solutions like FHE may shift from niche research to mainstream necessity. The success of Latica will depend not just on its technology, but on its ability to deliver on performance promises where others have stalled. If HEAL truly provides the acceleration needed, Latica could be at the forefront of a privacy first AI revolution. FHE has always sounded too good to be practical. Latica's hybrid model is ambitious but timely.

The funding, though modest by AI startup standards, could offer enough runway to prove viability. The pressure is now on Latica to show measurable performance gains that can persuade industries long wary of ICE privacy risks. Don't forget to like and share the story. Tip Vested Interest Disclosure. This author is an independent contributor publishing via our business blogging program. Hacker Noon has reviewed the report for quality, but the claims herein belong to the author. Hashtag DYO. Thank you for listening to this Hacker Noon story, read by Artificial Intelligence. Visit hackernoon.com to read, write, learn and publish.