EC-FHE: compute on data that stays encrypted.
Elliptic-curve homomorphic encryption computes directly on encrypted data. It never decrypts, even in use. The In-Use gap every other approach leaves open is closed by design.
Every breach happens in the same place: the In-Use plaintext gap.
Data at rest and in transit is already encrypted. The exposure is the moment it is decrypted to be used, and AI makes that moment constant.
AES-256 / KMS: disk & storage-level encryption
ProtectedTLS / HTTPS: network-layer encryption
ProtectedNone. Plaintext & keys exposed in memory during compute
ExposedWhat AI adds
Customer data leaks PII / IP the moment it is fed to a model.
Decryption windows open across training and inference.
Security fears block sharing between partners and institutions.
GDPR, the AI Act, and privacy law are all tightening at once.
EC-FHE computes without decryption, structurally closing the gap.
⚠ A decryption window every time data is used.
✓ Exposure eliminated at the source.
Run analytics and ML inference directly on encrypted data; results come back encrypted.
Power dashboards, model training, and decisions on regulated datasets.
Collaborate across teams and partners without handing over the raw data.
Fast enough for production. Encrypted computation runs at speed, so it works for every enterprise, not just a few.
- Never decrypted at any stage: at rest, in transit, or in use.
- No public key, evaluation key, or secret key ever lives on the server.
“Even if breached, there is nothing to take. Everything is ciphertext.”
EC-FHE solves speed and quantum-resistance at two separate layers.
Deep Circuit
Classic elliptic-curve (EC) encryption supports only addition and subtraction. That is too limited for real DB queries, machine learning, or statistics.
A proprietary algorithm implements multiplication and division, enabling deep computational circuits.
- SQL JOIN · GROUP BY · ML inference
- No noise, so no bootstrapping required
- Practical at low overhead vs plaintext
No-Key Protocol
EC math leaves a theoretical opening: a quantum Shor attack could derive the private key from a public key.
Public and evaluation keys are removed from the server entirely. There is no target left to attack.
- No public, evaluation, or secret key on the server
- Designed so the server view is information-theoretically independent of the plaintext (I(M;V) = 0)
- Designed to stay unexposed even to a computationally unbounded adversary (quantum included)
Lattice-based FHE earned quantum resistance through its algorithm but lost speed. 4Chains earned it through protocol, and kept the speed.
1.13ms encrypted queries. The speed ceiling of homomorphic encryption, removed by design.
Measured on Ubuntu 22.04 / coincurve (single core); throughput is per-core, derived from a 2-core end-to-end run (3,400 TPS) and scales linearly with cores. ops/s = homomorphic operations; TPS = end-to-end transactions.
Why it is structurally fast
Bootstrapping, lattice FHE's biggest bottleneck, is simply unnecessary.
With no keys on the server, key management and compute overhead approach zero.
Connects straight into Oracle, PostgreSQL, and SAP HANA. No re-platforming.
The value of FHE, on standard CPUs, without the GPUs.
Same capability. A different cost structure.
Working and being usable are not the same thing. Lattice FHE effectively needs GPU acceleration to reach practical throughput, which is why it often can't enter the air-gapped networks of banks, government, and enterprises. 4Chains runs on the standard CPUs you already operate, with no new hardware.
Cost figures are illustrative. Actuals vary by workload, configuration, and timing; GPU pricing and power assume typical data-center GPUs.
Trust earned by architecture, not by promises.
We don't ask you to trust a perimeter. Data stays encrypted even while it's used, keys are never exposed, and every computation can be proven correct without revealing the data behind it.
Encrypted in use
Data is never decrypted, whether at rest, in transit, or during computation. There is no plaintext window to attack.
No-Key Architecture
No public, evaluation, or secret key ever lives on the server, and there is no master copy of the data to steal.
Quantum-resistant by design
Built on post-quantum foundations engineered to hold against tomorrow's threats, not just today's.
Verifiable & auditable
Through Moduli Chain, security, compliance, and partners can verify outcomes without ever seeing the underlying data.
Data stays in place
Compute where the data lives. Nothing is pooled, copied, or moved, which supports residency and data-minimization obligations.
Built for regulated sectors
Designed around the privacy obligations of finance, healthcare, and the public sector from the start.
We're glad to walk your security team through the architecture and controls in a technical review.
Two layers, each secured by the method that fits.
Data and identity face different threats, so 4Chains secures each with the approach built for it. One platform, two layers.
TorusDB · EC-FHE
Compute directly on encrypted data. With no keys on the server, the server's view is designed to be information-theoretically independent of the plaintext, so there is nothing to derive, even for a quantum adversary.
PrivID for PQC · CRYSTALS-Dilithium
Authenticate and sign with lattice signatures that stay unforgeable even against a full-scale quantum adversary. Passing a check proves the signature is valid and bound to the right user-service context.
Post-quantum unforgeability applies to PrivID's signing. Its identifier-privacy layer rests on classical assumptions today; full post-quantum privacy is on the roadmap.
See EC-FHE in action.
From encrypted storage to ML inference: the whole pipeline, never decrypted.