Lattica develops a platform that enables privacy-preserving AI inference using Fully Homomorphic Encryption (FHE). The company addresses the challenge organizations face when trying to leverage AI while protecting sensitive data by allowing computation on encrypted data without decryption. The platform is built on applying machine learning optimization techniques to FHE, including parallel computation, tensor operations, and hardware acceleration. Lattica integrates directly with PyTorch and other standard ML frameworks, allowing developers to implement encrypted AI inference without requiring cryptography expertise. The system is designed for AI inference workloads and includes optimizations across the entire stack, from model-aware algorithmic design to hardware-level improvements. The company's infrastructure dynamically manages compute resources and enables AI providers to deploy encrypted inference as a service that scales based on demand. Lattica's approach focuses on making FHE practical for real-world AI workflows by treating it as a machine learning infrastructure problem rather than purely a cryptographic challenge. The team combines expertise in cryptography, machine learning, and cloud infrastructure, working at the intersection of theoretical cryptography and practical implementation. Their development includes CUDA-based GPU optimization for homomorphic encryption operations and cryptographic components specifically designed for AI workloads.