Fairmath offers a high‑performance homomorphic encryption platform that enables arbitrary computation on encrypted data, providing provable privacy guarantees for AI training, inference, and blockchain smart contracts. Its SIMD‑optimized engine delivers up to 1000× faster evaluation than prior FHE schemes, allowing enterprises to process sensitive data without exposing plaintext.
Funding
Funding not disclosed
Founders
Product
Problem
AI models and blockchain applications often require access to raw data, creating privacy risks that limit their use in sensitive industries such as finance, healthcare, and enterprise data processing. Existing cryptographic solutions are either too slow or support only limited computations, preventing practical deployment of privacy‑preserving services.
Solution
Fairmath provides a next‑generation homomorphic encryption (FHE) platform that enables arbitrary function evaluation on encrypted data with high efficiency. By leveraging advanced mathematical constructions, the system delivers up to 1000× faster evaluation compared with earlier FHE generations while supporting vectorized (SIMD) processing of thousands of data points simultaneously. This allows developers to train AI models, run inference queries, and execute confidential smart contracts without ever exposing plaintext data. The platform offers provable privacy guarantees, making it suitable for enterprise AI pipelines and blockchain solutions that require strict data confidentiality.
Target Audience
Primary customers are enterprises and developers building AI services or blockchain applications that handle sensitive data, including financial institutions, healthcare providers, and decentralized finance platforms.
Features
- 1000× faster homomorphic evaluation versus 3rd‑ and 4th‑generation FHE schemes
- Support for arbitrary function computation on encrypted inputs
- SIMD vectorized processing that handles thousands of values in parallel
- Integrated primitives for private AI training and inference workflows
- Cryptographic infrastructure for confidential transactions and smart contracts on blockchain networks
- Mathematical privacy guarantees backed by formal security proofs