Why CKKS, not BFV / TFHE.
Matching orders is arithmetic over prices — not boolean gates. CKKS (Cheon–Kim–Kim–Song) natively supports approximate real-number arithmetic with SIMD-style packing, making it the right tool for the financial workload. BFV/BGV make exact integer math more expensive; TFHE optimizes for boolean circuits.
Parameters.
What we actually do with it
Six live workloads. All ship today, all benchmarked in production.
Confidential matching
Price and size ciphertexts cross in a CLOB without either counterparty seeing the other. Fills decrypt only for trade parties.
Dark-pool orders
Institutional orders posted as FHE ciphertexts. Market makers quote against encrypted depth; no pre-trade leakage.
Encrypted portfolio analytics
Risk, P&L, and exposure reports computed on encrypted positions. The analytics service never sees plaintext holdings.
Blind credit scoring
Lenders evaluate encrypted balance, income, and on-chain history. Only the yes/no decision — and the applicant — see the underlying data.
Private order book depth
Level-2 depth available to subscribers as ciphertexts; aggregated totals decrypt publicly, but individual orders stay hidden.
MPC + FHE compliance
Sanctions screen and Travel Rule evaluate encrypted counterparty data. "Is this address on the SDN list?" answered without revealing the address.
Architecture
FHE is a coprocessor. Most hot-path actions remain plaintext; only the confidential lanes traverse the CKKS engine.
Client-side encryption
Orders encrypted in the browser / mobile SDK with the tenant's CKKS public key. Plaintext never leaves the user device.
FHE coprocessor
GPU-accelerated CKKS evaluator runs matching, aggregation, and risk circuits. The coprocessor sees ciphertexts only — no key material.
Threshold decryption
Only results addressed to counterparties are decrypted, via an MPC threshold of the decryption key. The platform can never unilaterally decrypt.
Performance, honestly.
FHE is not free. A single ciphertext multiplication at ring-14 costs ~10ms on CPU, ~0.5ms on GPU. We use FHE where confidentiality matters more than microseconds — dark-pool books, encrypted analytics, private scoring — and plaintext CLOBs for commodity order flow.
Paired with ZAP.
FHE keeps the computation private; ZAP publishes succinct proofs that the computation was correct. Together they give the best of both worlds: nothing is revealed, but everything is verifiable.
Compute on the cipher.
Integrate FHE order types via our SDK. Your clients' orders stay encrypted end-to-end.