The FHE landscape in 2026 has fragmented into specialized verticals. Fully homomorphic encryption is no longer a single technology with a single use case—it is an enabling primitive that different companies have applied to fundamentally different problems. Duality Technologies builds privacy-preserving data collaboration platforms for financial services and government analytics. Enveil built encrypted search under its "ZeroReveal" brand. H33 builds post-quantum authentication infrastructure that processes 2.15 million authentications per second on production hardware. All three use FHE. None of the three are interchangeable.
This comparison is not about declaring winners and losers across unrelated domains. It is about helping engineering teams understand what each platform actually does—and why choosing the wrong one for authentication would be a costly mistake.
What Are Duality & Enveil?
Duality Technologies
Duality Technologies is an enterprise FHE company that spun out of academic research at NJIT and was part of DARPA's DPRIVE (Data Protection in Virtual Environments) program. The company developed OpenFHE, the open-source successor to the PALISADE library, and sells a commercial product called Duality Platform built on top of it. Duality's focus is privacy-preserving data collaboration—enabling multiple organizations to compute analytics over combined datasets without revealing their raw data to each other. The primary use cases are data clean rooms for financial services, healthcare record analysis, and government intelligence sharing.
Duality Platform is well-suited to its intended domain. It provides tools for data scientists to run queries, aggregations, and machine learning workloads over encrypted data from multiple parties. Performance characteristics reflect this workload: analytics queries typically complete in seconds to minutes depending on dataset size and computation complexity. This is acceptable for batch analytics. It is entirely unsuitable for real-time authentication.
Enveil
Enveil built a product called ZeroReveal, focused narrowly on encrypted search—querying encrypted databases without decrypting the data or revealing the search terms. The company targeted use cases where the query itself is sensitive: law enforcement running name checks against private databases, intelligence agencies searching commercial datasets, and financial institutions screening transactions against watchlists. Enveil has seen limited public activity in recent periods following acquisition and restructuring, and its product footprint remains focused on encrypted search rather than general-purpose FHE computation.
For simple encrypted queries, Enveil demonstrated sub-second performance. More complex searches extended into the seconds range. Like Duality, these timings are reasonable for their intended use case but irrelevant to authentication workloads.
Where They Fall Short for Authentication
Both Duality and Enveil built legitimate products for legitimate use cases. Neither product can be used for authentication. The reasons are structural, not incremental.
Authentication requires five capabilities in a single pipeline: encrypted biometric matching, zero-knowledge proof of correct computation, post-quantum digital signatures for attestation, batched processing for throughput, and sub-millisecond latency for real-time use. Duality provides one of these (encrypted computation) with multi-second latency. Enveil provides none of them—encrypted search is a different primitive entirely. Assembling an authentication stack from either platform would require building the other four capabilities from scratch.
No Post-Quantum Signatures
Neither Duality nor Enveil includes post-quantum digital signatures in their pipelines. Duality's FHE layer is lattice-based and believed quantum-resistant, but without Dilithium or equivalent signatures for attestation, any authentication system built on top would be vulnerable to quantum attack at the signature layer. H33 uses NIST FIPS 204 (ML-DSA/Dilithium) for every attestation—191 microseconds per batch—making the full pipeline post-quantum secure end to end.
No Biometric Pipeline
Neither platform provides biometric template enrollment, encrypted template storage, SIMD-batched matching, or threshold decryption. Duality's analytics tools could theoretically compute inner products over encrypted biometric vectors, but the setup work—batching 32 users per ciphertext via CRT slots, storing templates in NTT form, managing key lifecycles—would amount to building H33 from scratch on top of Duality's primitives.
No Zero-Knowledge Proofs
Neither Duality nor Enveil includes zero-knowledge proof generation or verification. H33's pipeline includes STARK-based ZKP with in-process DashMap caching that resolves in 0.062 microseconds per lookup. This proves correct computation to relying parties without revealing biometric data. There is no equivalent in either Duality's analytics platform or Enveil's search product.
H33's Full-Stack Approach
H33 is purpose-built for one job: post-quantum biometric authentication at production scale. A single API call triggers the complete pipeline—BFV-encrypted biometric matching across 32 users in a SIMD-batched ciphertext, zero-knowledge proof verification, and NIST FIPS 203/204 compliant Dilithium attestation. The full sequence completes in 36 microseconds per authentication on AWS Graviton4 hardware.
What Ships in One API Call
BFV encrypt with SIMD batching (32 users per ciphertext, N=4096, single 56-bit modulus). Montgomery NTT with Harvey lazy reduction—zero division in the hot path. NTT-domain fused inner product with one final INTT. Threshold decryption with zero plaintext exposure. SHA3-256 ZKP cache lookup in 0.062µs. ML-DSA Dilithium sign+verify in 191µs. Total: 967µs for 32 users. No assembly required. No PhD needed.
The architectural difference is not about raw FHE speed. It is about vertical integration. Duality optimizes for flexible analytics across arbitrary datasets. Enveil optimizes for encrypted database search. H33 optimizes for exactly one computation—biometric inner product matching—and builds every layer of the stack around that single operation. The result is that H33's FHE batch completes in under a millisecond while analytics platforms measure their workloads in seconds.
Pre-computed NTT-form templates, batch CBD sampling, pre-NTT public keys at keygen, and fused inverse Montgomery post-processing are optimizations that only make sense for a dedicated authentication workload. They would not help a general-purpose analytics platform. This is the advantage of vertical specialization.
Head-to-Head Comparison
| Capability | Duality | Enveil | H33 |
|---|---|---|---|
| Primary Use Case | Privacy-preserving analytics | Encrypted database search | Full-stack authentication |
| FHE Implementation | OpenFHE (BFV/BGV/CKKS) | Proprietary (search-optimized) | Custom BFV + CKKS (Rust, production-tuned) |
| Typical Latency | Seconds to minutes | Sub-second to seconds | 967µs batch / 36µs per auth |
| Auth Throughput | Not applicable | Not applicable | 2.15M auth/sec (96 cores) |
| Post-Quantum Signatures | None | None | ML-DSA (Dilithium) — 191µs |
| Zero-Knowledge Proofs | None | None | STARK + DashMap cache (0.062µs) |
| Biometric Authentication | None (analytics only) | None (search only) | 32-user SIMD batch, NTT-form templates |
| NIST PQC Compliance | No (FHE layer only) | No | FIPS 203 (Kyber) + FIPS 204 (Dilithium) |
When to Use Each
These three platforms solve different problems. The right choice depends entirely on what you are building.
Use Duality When Encrypted Analytics
- You need multi-party data collaboration where organizations compute over combined datasets without sharing raw data
- Your use case is batch analytics—aggregations, machine learning, statistical analysis—where seconds-to-minutes latency is acceptable
- You are building data clean rooms for financial services, healthcare, or government and need compliance with data-sharing regulations
- You want to leverage OpenFHE with commercial support and managed infrastructure around it
Use Enveil When Encrypted Search
- You need to search encrypted databases without revealing your query terms to the database operator
- Your use case involves sensitive lookups—watchlist screening, law enforcement queries, intelligence analysis—where the search itself must remain private
- You require a narrow, single-purpose tool for encrypted search and do not need analytics, authentication, or general FHE computation
Use H33 When Production Authentication
- You need FHE-based biometric authentication with encrypted template matching and zero plaintext exposure
- You require post-quantum security across the entire pipeline—not just the FHE layer, but signatures, key exchange, and attestation
- Your throughput requirements exceed 10,000 auth/sec and you need proven performance on commodity cloud hardware
- You need ZKP attestation that proves correct computation to relying parties without revealing biometric data
- You want one API call that handles the full authentication pipeline—no integration of separate FHE, ZKP, and signature libraries
- You need NIST FIPS 203/204 compliance for regulatory or procurement requirements
Duality and Enveil are not failed attempts at what H33 does. They are successful implementations of different applications of homomorphic encryption. Duality's data clean room technology solves a real problem for enterprises that need to collaborate on sensitive data. Enveil's encrypted search addressed a genuine need in intelligence and law enforcement. The issue is not that these products are bad—it is that they cannot be repurposed for authentication any more than a database can be repurposed as a web server. H33 exists because authentication requires a vertically integrated stack—FHE, ZKP, and post-quantum signatures fused into a single pipeline—and no analytics or search platform provides that. 2,227 tests and 108 patent claims reflect the depth of that specialization.
The FHE market will continue to fragment into specialized verticals. Analytics platforms will serve analytics. Search tools will serve search. Authentication infrastructure will serve authentication. The mistake is assuming that because two products use the same underlying cryptographic primitive, they are substitutes for each other. They are not. The 36-microsecond gap between H33's per-authentication latency and the seconds-to-minutes timings of analytics workloads is not a performance difference—it is a category difference.
H33 ships the full authentication stack: FHE biometrics, zero-knowledge proofs, and post-quantum attestation in a single API call. 2.15 million times per second. On production hardware. Today.