Technology
How It Works
CypherAI uses production-grade homomorphic encryption (FHE) to enable AI inference on data that stays encrypted throughout the entire process. No decryption at any stage. Mathematical guarantee, not contractual promise.
From Trust-Based to Math-Based Security
Traditional enterprise security relies on policies, access controls, and perimeter defense. But when data must be processed in the cloud, it is decrypted - creating an unavoidable exposure point. This is why defense and financial institutions cannot leverage AI on their most sensitive datasets.
Homomorphic encryption changes the equation entirely. It enables computation directly on encrypted data - without ever decrypting it. The cloud operator processes ciphertext and returns encrypted results. Only the data owner holds the keys.
This is the shift CypherAI delivers: mathematically-enforced encrypted LLM inference that enables classified and regulated data to flow through AI infrastructure with zero plaintext exposure.
Traditional Encryption
CypherAI Encrypted Inference
Zero plaintext exposure at any stage - mathematical guarantee
Encrypted LLM Inference Architecture
End-to-end encrypted pipeline from prompt to response. The LLM provider never sees plaintext at any stage.
The Sovereign Compute Model
Key Management
Encryption keys never leave customer control. Raw data remains inside the perimeter. Mathematical guarantee.
Encrypted Processing
Data is processed as ciphertext. The host provider has zero visibility into underlying values. From trust-based to math-based security.
Why Not Confidential Computing or VPCs?
Confidential Computing (TEEs)
Data is still decrypted inside the enclave. Side-channel attacks, firmware vulnerabilities, and the cloud provider still has physical access. Trust-based, not math-based.
VPC / Isolated Deployments
Data is decrypted during processing. Insiders, admins, and infrastructure operators can access plaintext. Compliance is contractual, not cryptographic.
CypherAI (FHE)
Data is never decrypted. Computation runs directly on ciphertext. Security is mathematical, not contractual. Post-quantum resilient (TFHE).
The 400× Breakthrough
For decades, homomorphic encryption promised computation on encrypted data. But 100-1000× overhead made production deployment impossible.
Our breakthrough: optimizing TFHE at the representation level - not just implementation - achieved a 400× speedup over industry standard libraries, shifting encrypted compute from theoretical possibility to deployed reality.
The Old Reality
Traditional HE implementations suffered from massive overhead, keeping encrypted computation trapped in the research lab and unusable for real-time applications.
The CypherAI Breakthrough
Real-time encrypted LLM inference that actually works. 400× faster than state-of-the-art baselines. Q2 2026: GPU acceleration targeting 50-100× additional speedup.
See the Numbers
Review our independently-validated benchmark results and production performance metrics.