As blockchain technology matures, the focus is shifting from scalability and interoperability to privacy. Early Web3 privacy solutions relied heavily on anonymity tools like mixers or shielded transactions. Today, however, privacy is expanding into a broader frontier -encrypted computation. This means performing computations on-chain without revealing the data involved, enabling use cases that were previously impossible.
This evolution is more than a technical milestone. With tightening global laws, building applications that are both private and compliant is becoming essential.
Enter four key players in this space: COTI , Aleo, Aztec , and Fhenix. Each offers a distinct approach to encrypted computation, targeting different trade-offs in speed, compliance, programmability, and privacy depth. Let’s explore what sets them apart and how they might shape the next generation of private smart contracts.
Project Overviews: What They’re Building
COTI: A privacy-centric Layer 2 built on Ethereum using Garbled Circuits and MPC (Multi-Party Computation). COTI aims for high efficiency and regulatory alignment, achieving up to 1,000 TPS for native transactions and around 40 TPS for encrypted contracts. Its architecture balances confidentiality with compliance.
Aleo: A Layer 1 blockchain tailored for full-stack private applications. Developers use its native language, Leo, to write privacy-preserving programs that compile into zero-knowledge circuits. Aleo’s design allows expressive and deeply private applications but demands a steeper learning curve.
Aztec: A ZK-rollup on Ethereum with a hybrid model that supports both public and private smart contracts. Developers can selectively encrypt parts of their contracts, combining privacy where necessary with the transparency of the Ethereum ecosystem. Notably known for zk.money.
Fhenix: Built on Ethereum, Fhenix introduces Fully Homomorphic Encryption (FHE) to Web3. FHE allows computation directly on encrypted data without needing decryption, offering deep privacy. Although currently slower, Fhenix wraps this tech in Solidity-like tooling to smooth the dev experience.
Under the Hood: Technical Approaches Compared
Each project takes a different path to privacy, affecting their performance, programmability, and developer accessibility:
•COTI uses Garbled Circuits + MPC, which allows for efficient encrypted computation with limited overhead. Off-chain execution between parties generates encrypted outputs posted on-chain. This model delivers high throughput while keeping logic auditable.
•Aleo uses ZKPs and a proprietary language, Leo, optimized for zero-knowledge circuit programming. This grants fine-grained privacy but requires specialized developer knowledge.
•Aztec implements a zkSNARK hybrid architecture inside a ZK-rollup. Developers decide which parts of a contract are encrypted, using familiar Ethereum tooling, offering strong modularity.
•Fhenix brings FHE to smart contracts, allowing encrypted data to be processed without revealing it. It’s the most privacy-heavy approach but faces significant computational overhead. However, developer tools aim to abstract that complexity.
Where they stand:
COTI: Speed, compliance, and practical UX.
Aleo: Maximum privacy, high customizability.
Aztec: Best of both worlds with hybrid flexibility.
Fhenix: Cutting-edge encryption for high-stakes data privacy.
Ecosystem and Use Case Fit
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COTI is purpose-built for industries that require both privacy and audibility, like finance, identity verification, and healthcare. Its infrastructure is aligned with regulatory-grade encrypted computation, supporting DeFi protocols, fintech apps, and institutional systems requiring compliance-ready privacy. Through its Compliance Oracle and zero-leakage encrypted smart contracts, COTI provides verifiable privacy that satisfies both developers and regulators.
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Aleo has built a thriving dev community around privacy-first apps, from games and identity protocols to decentralized voting systems. Its grant programs and educational tooling make it attractive to pioneers.
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Aztec powers tools like zk.money and is building toward a full-fledged ZK stack for Ethereum. Its appeal lies in gradual privacy adoption within familiar frameworks.
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Fhenix targets complex, data-sensitive use cases such as AI inference, private auctions, and data science on-chain. Though still early, its tech has drawn interest from developers exploring frontier use cases.
Final Thoughts: Is There a Winner Yet?
In this privacy arms race, there is no one-size-fits-all solution. Each project is optimized for a different version of the future:
COTI shines in speed and regulatory clarity. It’s perfect for developers who need fast, scalable, and legally compatible infrastructure.
Aleo is for developers who want full privacy and full control, regardless of regulation.
Aztec serves those who want a balanced approach within the Ethereum ecosystem.
Fhenix is exploring what’s possible with next-gen encryption, even if it’s early and slow.
Privacy is becoming a necessity in Web3. Whether you’re building the next DeFi protocol, protecting user identities, or crunching encrypted AI models, the path you take depends on your priorities. Try them, break them, build with them because privacy’s future is being written now.
ALSO READ: COTI V2’s Secret Weapon: Garbled Circuits Explained for the Web3 Era
