Fully homomorphic encryption
Run computation directly on ciphertext with TFHE, CKKS, and BGV/BFV. Data is never decrypted to be used.
Fully homomorphic encryption and threshold FHE let you run analytics and risk on data that is never decrypted, with regulator-grade disclosure when required. Confidentiality and auditability stop being a trade-off.
Institutions need data kept private and a clear record an examiner can trust. Today they pick one. Plaintext data sitting in analytics pipelines is a standing liability, and privacy that no one can inspect fails the audit. The right answer is both, by construction.
Every system that decrypts data to use it widens the blast radius of a breach and the surface a regulator scrutinizes.
Privacy that cannot be inspected or disclosed under lawful process does not satisfy supervisors. It shifts risk rather than removing it.
Analytics, vendors, and partners each need access to compute. Every copy decrypted for them is a new place to lose control.
Confidentiality cannot mean immunity. The system must produce data under a valid order without a permanent backdoor.
A working cryptographic stack for computing on data that stays encrypted, with compliance built into the same system rather than bolted on after.
Run computation directly on ciphertext with TFHE, CKKS, and BGV/BFV. Data is never decrypted to be used.
Distributed decryption across a quorum, with no single key holder who can unilaterally see the data. This is the frontier, and the hardest part.
A regulator forced-decryption quorum reveals exactly what a lawful order requires, recorded and auditable, with no standing backdoor.
Compliant transaction privacy that shields participants while preserving the ability to prove legitimacy and exclude illicit funds.
Prove a statement is true, such as a balance, an eligibility, or a policy check, without revealing the underlying data.
Scoring, aggregation, and risk models that execute over encrypted inputs, so insight never requires exposure.
Real cryptography you can read and verify, not slideware.
Across fully homomorphic encryption, threshold cryptography, and confidential computing.
The FHE primitives are published in the open, so the cryptography can be audited rather than trusted on faith.
Threshold FHE for regulatory compliance and TFHE, developed in the open and grounded in published work.
License the IP, resell it under your brand, or co-build with our team. Deployable into any regulated market.
Book a discovery call →Get a tailored walkthrough and a straight answer on fit, timeline, and cost for your institution.
Model-agnostic · integrates with the AI platforms you already trust
ACM Global Tech is an ecosystem partner of Hanzo.ai and Lux Network and a member of the W3A (Web3 Alliance), pairing enterprise-grade agentic AI with institutional tokenized-finance and settlement infrastructure.
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