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Home » Lattica Emerges From Stealth With FHE Platform for AI
Cybersecurity

Lattica Emerges From Stealth With FHE Platform for AI

adminBy adminApril 25, 2025No Comments2 Mins Read
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Lattica emerged from stealth mode this week with a platform that leverages fully homomorphic encryption (FHE) to enable AI models to process encrypted data. 

FHE enables the processing of encrypted data without the need to decrypt it first, making it useful for situations where sensitive data needs to be processed without being exposed.

The Lattica platform can be used by AI providers to host models, manage access, and allocate resources, which can then be used by end users to run queries that remain encrypted and thus are never exposed to the AI provider. 

The Lattica solution leverages Homomorphic Encryption Abstraction Layer (HEAL), a cloud-based service that enhances FHE performance and standardizes its acceleration. 

This component serves as a bridge between FHE software and hardware, including CPUs, GPUs, TPUs, as well as ASIC and FPGA chips. 

The company says its platform is ideal for sectors such as finance, healthcare and government, where data privacy and security concerns may limit the adoption of AI. 

Lattica has raised $3.25 million in a pre-seed funding round led by Konstantin Lomashuk’s Cyber Fund.

“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,” said Rotem Tsabary, founder and CEO of Lattica. “We’re enabling practical FHE by developing a solution that is tailor made for neural networks.”

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Related: Cryptography Firm Zama Raises $73 Million for FHE Solution

Related: DataKrypto Launches Homomorphic Encryption Framework to Secure Enterprise AI Models

Related: Cyber Insights 2025: Quantum and the Threat to Encryption

Related: Jericho Security Gets $15 Million for AI-Powered Awareness Training



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