A query is encrypted directly in your browser using FHE.
This ensures that Lattica never sees or stores your raw data, only its encrypted form.
Fully Homomorphic Encryption (FHE) is an advanced cryptographic technique that enables computations on encrypted data without ever decrypting it.
This means that even when data is processed by AI models, cloud services, or third parties, its confidentiality remains intact.
Traditional encryption protects data at rest or in transit but require decryption for processing.
In Lattica we build an AI inference platform that runs AI models on encrypted queries using FHE:
A query is encrypted directly in your browser using FHE.
This ensures that Lattica never sees or stores your raw data, only its encrypted form.
The AI model runs directly on the encrypted query without first decrypting it.
Lattica cannot see your input, output, or intermediate results during computation.
The model returns an encrypted prediction.
Decrypt and view the final prediction on your browser.
While FHE is a breakthrough technology in privacy-preserving computation, several challenges have slowed its adoption:
FHE operations require significantly more processing power conpared to traditional computing, making them slower and more resource-intensive.
Most existing FHE tools originate from applied academic research and are designed for general-purpose use, making them inefficient for real-world applications.
Enterprises face challenges integrating FHE due to a lack of readily available cryptographic expertise.
The absence of standardization across the FHE stack creates compatibility issues, making integration complex and time-consuming.
Our solution, expertise and attention are at making FHE work good at scale for neural networks inference. This means we optimize the whole stack:
A system for deploying and managing neural networks, supporting both a web interface and API-based interactions. It integrates with the standard ML stack and enables dynamic compute allocation and access management. We call this FHE-as-a-Service.
Handles key generation, encryption, and decryption. Running across multiple platforms, from browsers to Python and mobile.
The core of our backend, responsible for executing neural networks on encrypted queries. This is where we apply algorithmic optimizations tailored to both network architecture and encryption security parameters.
A software-hardware interface that enables the FHE Inference Engine to run efficiently on both off-the-shelf accelerators (e.g. GPUs) and designated FHE hardware.