The Year Privacy Became Non-Negotiable

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Institutional traders moved $2.3 billion through private DeFi channels in Q3 2025 alone, according to recent blockchain analytics, marking the inflection point where confidential transactions transitioned from experimental to essential. The transparency that made blockchain revolutionary has revealed its limitations: every trade position, every strategy, every wallet balance sits exposed on public ledgers where competitors and MEV bots extract value.

2025 marked the year encryption technologies like Fully Homomorphic Encryption (FHE) and zero-knowledge proofs matured from academic concepts into production infrastructure. As our CEO Guy Itzhaki observed earlier this year, "The next generation of DeFi will be built on encrypted computation, where institutions can operate with the same confidentiality they expect from traditional finance while maintaining blockchain's transparency guarantees."

At Fhenix, we've been building toward this moment since our founding. With our CoFHE, an FHE-based coprocessor now live on Ethereum, Arbitrum and Base testnet chains and processing real encrypted transactions, we're witnessing firsthand how the privacy landscape evolved in 2025. This recap examines where the ecosystem stands, how different approaches to privacy compare, and what developers should consider when building confidential applications.

Understanding the Privacy Landscape

Private DeFi refers to decentralized financial applications (DeFi apps) where sensitive data is private by using different techniques to keep transaction details, user positions, and trading strategies confidential while maintaining the verifiability and composability that makes DeFi functional. one of the techniques is FHE which is based on match/cryptography.

Unlike traditional DeFi where every swap, loan, and liquidity position appears on public block explorers, privacy-preserving protocols encrypt sensitive data while still allowing smart contracts to execute operations and validators to verify correctness. The technology landscape spans multiple approaches: Fully Homomorphic Encryption (FHE) enables computation directly on encrypted data, zero-knowledge proofs verify transactions without revealing details, and Trusted Execution Environments (TEEs) create confidential execution spaces within specialized hardware.

The sector emerged from real pain points that cost the industry billions. According to research from leading MEV protection providers, frontrunning costs traders an estimated $1.2 billion annually across major DEXs. Institutional participants need confidentiality for regulatory compliance under frameworks like GDPR and MiFID II. Competitive traders cannot afford to broadcast positions to MEV bots and competitors who can extract value within milliseconds. These challenges drove the privacy innovations we saw accelerate in 2025.

Key Trends That Defined 2025:

1. Privacy becoming a foundational requirement

Institutional capital began treating privacy not as an optional enhancement but as a baseline requirement for settlement, trading, and credit. Confidential order flow, private balance sheets, and encrypted risk calculations became central themes across major DeFi research initiatives and pilot deployments.

Within this broader trend, Fully Homomorphic Encryption (FHE) emerged as one of several technologies enabling on-chain confidentiality:

• FHE reached practical readiness through early-stage deployments proving that encrypted computation could operate at meaningful throughput and latency.
• Fhenix’s CoFHE went live across Ethereum, Arbitrum, and Base testnets, offering single-line Solidity integration for encrypted execution.
• As Guy Zyskind, Fhenix founder, noted during the testnet launch: “FHE has been theoretically possible for decades - CoFHE demonstrates how close we are to practical, composable encrypted smart contracts.”

Rather than replacing other privacy approaches (ZK proofs, MPC relays, private order flow), FHE added a new dimension by enabling computation directly on encrypted state.

2. Institutional adoption accelerating infrastructure upgrades

Traditional finance firms increasingly explored on-chain settlement rails - but only under confidentiality guarantees. Requirements included private order books, hidden collateral balances, regulatory-aligned selective disclosure, and compliance-ready audit mechanisms.

Partnerships like Fhenix × BIPROGY illustrated how institutional demand for privacy-preserving DeFi infrastructure accelerated regulatory-compliant blockchain adoption throughout 2025.

3. Privacy layers becoming modular and composable

2025 marked the shift from “privacy chains” to privacy modules. Developers demanded privacy without fragmenting liquidity, compatibility with the EVM, and the ability to upgrade existing protocols rather than redeploy them.

CoFHE reflected this trend by allowing developers to add encrypted execution to existing Ethereum, Arbitrum and Base contracts - maintaining composability while upgrading confidentiality. This modularity proved essential as DeFi infrastructure matured and UX expectations rose.

Who Needed Privacy Solutions in 2025

Early-Stage Protocols: DeFi protocols experimenting with novel mechanisms needed to prevent strategy extraction by competitors. A new AMM design or yield optimization strategy becomes worthless if competitors can clone it by watching transaction patterns on block explorers. Privacy tools became essential for protecting intellectual property during development phases when competitive advantages are most vulnerable.

Growth-Stage Protocols: Mid-size protocols handling $50M-500M TVL faced sophisticated MEV extraction and sandwich attacks that drained value from users. Research showed that protocols crossing the $100M TVL threshold experienced a sharp increase in targeted MEV attacks. At this scale, protecting users from frontrunning became essential for retention, driving adoption of encrypted execution solutions.

Institutional Participants: Traders managing $100M+ positions could not operate with full transparency. Regulated entities needed confidential audit trails that satisfied compliance requirements without exposing commercial data on public chains. Market makers required private inventory management to prevent information leakage that competitors could exploit. Confidential smart contracts shifted from nice-to-have features to mandatory infrastructure.

Key Adoption Signals We Observed:

• Protocol TVL attracting consistent MEV extraction (visible through zero-slippage sandwich attacks)
• User requests for private trading options and complaints about frontrunning losses
• Institutional inquiries explicitly mentioning confidentiality requirements
• Competitive advantages depending on strategy secrecy that public chains compromised
• Regulatory compliance requiring privacy-preserving data handling under GDPR or financial regulations

What Privacy Unlocked in 2025:

Regulatory compliance: Confidential transactions enabled GDPR compliance and institutional KYC without exposing user data on-chain, opening markets previously closed to transparent blockchain applications.

Competitive protection: Protocols could launch innovative mechanisms without immediately revealing strategies to competitors who monitor mempool activity and contract interactions.

Premium market access: Whale traders and institutions willing to pay for privacy features created new revenue opportunities. According to market research, institutional clients typically paid 2-3x standard fees for confidential execution guarantees.

Private payments: Users and institutions could transfer value without publicly exposing balances, counterparties, or payment flows on-chain - unlocking use cases like payroll, B2B settlements, and consumer payments that were previously impossible on transparent blockchains.

How We Evaluate Privacy Solutions

When developers ask us which privacy approach suits their needs, we guide them through several critical dimensions:

Technical Foundation:

1. Cryptographic approach and maturity: Whether the solution uses FHE, zero-knowledge proofs, TEEs, or multi-party computation (MPC), and how production-ready the technology is with live testnet deployments
2. EVM compatibility and developer experience: How easily developers can integrate privacy features using familiar Solidity workflows versus learning new languages like Cairo or Noir
3. Composability with existing DeFi: Whether the solution fragments liquidity onto isolated chains or enables private interaction with mainnet protocols and existing liquidity pools
4. Decentralization and trust assumptions: The degree to which privacy relies on trusted parties, specialized hardware, or cryptographic guarantees alone
5. Performance and costs: Transaction finality times, gas costs, and computational overhead compared to standard DeFi operations on Ethereum mainnet

Ecosystem Factors:

1. Active ecosystem and production usage: Number of live integrations, TVL in private applications, developer activity measured by GitHub commits and documentation quality
2. Specific privacy guarantees delivered: What exactly stays private (amounts, participants, contract state, transaction existence) and what remains visible to validators or observers

Common Tradeoffs:

Ease of use vs. customization: Solutions with single-line integration like our CoFHE offer simplicity with minimal code changes, while building custom zero-knowledge circuits provides granular control but requires specialized cryptographic expertise.

Universal privacy vs. specialized features: Comprehensive encryption platforms protect all contract state but may introduce overhead, compared to targeted MEV protection tools that solve narrow problems efficiently.

Integrated vs. isolated: Privacy layers that integrate with existing chains preserve composability but may have narrower scope, while dedicated privacy L2s provide end-to-end solutions but require ecosystem migration and liquidity fragmentation.

The 2025 Privacy Landscape: Key Players

Fhenix: FHE Coprocessors on Ethereum, Arbitrum and Base

We built Fhenix to bring Fully Homomorphic Encryption to EVM-compatible chains through our CoFHE coprocessor. Backed by $22M in funding, we represent the FHE infrastructure that maintains standard EVM workflows while encrypting computation end-to-end without trusted hardware dependencies.

Our Approach:CoFHE enables developers to write privacy-preserving smart contracts with single-line Solidity additions. The coprocessor is live on Arbitrum, Ethereum and Base testnet, processing encrypted computations with real transactions.

Best suited for: DeFi protocols requiring encrypted computation on sensitive data without trusted parties - confidential trading, private DAOs, encrypted token balances, and MEV-resistant applications where data must remain encrypted during processing. Solutions for institutions running compliant private transactions on Ethereum.

Key advantages:

• One-line Solidity integration: CoFHE enables encrypted smart contracts with minimal code changes using familiar EVM tools. According to our developer documentation, teams can add FHE encryption to existing contracts in hours rather than weeks of rewrites.
• Non-interactive encryption: FHE operates without coordination between parties, unlike multi-party computation which requires interactive protocols. This simplifies deployment and eliminates coordination overhead.
• No trusted hardware dependencies: Unlike TEEs that rely on specific chipsets, FHE keeps data encrypted throughout computation using pure cryptographic guarantees. As Guy Zyskind explains, "TEEs introduce hardware trust assumptions that institutional compliance teams struggle to accept. FHE provides mathematical certainty."
• Complete data privacy: Computations happen on encrypted data that never needs decryption on-chain, preventing exposure at any stage. Contract state remains encrypted even during validation.
• Ready to test on Ethereum, Arbitrum and Base: Live testnet infrastructure processing real transactions today, with additional chain integrations coming in 2026.

Current limitations:

• FHE operations require more processing than standard execution, though CoFHE offloads heavy cryptographic work
• The ecosystem of FHE-based applications is still building compared to established L2s with years of tooling

Developer feedback: Early builders integrating CoFHE reported that adding encryption to existing contracts took hours rather than weeks. One DeFi protocol encrypted their order book with just 47 lines of modified Solidity, preserving full composability with existing liquidity pools.

Aztec Network: Privacy-Native L2

Aztec operates as a privacy-focused Layer 2 on Ethereum using zero-knowledge proofs. Their Ignition Chain launched on mainnet in November 2025 as a fully decentralized L2 with over 500 validators processing confidential transactions.

Their approach: Building privacy-first applications from the ground up on a complete privacy-native blockchain environment.

What they offer: Fully decentralized L2 with native privacy from network launch, zero-knowledge proof architecture keeping transaction details confidential. Previous Aztec Connect achieved $17M TVL and 100,000+ wallets before sunset.

Key tradeoff: Requires building on separate L2 rather than integrating with existing Ethereum mainnet contracts, fragmenting liquidity. Aztec Connect was sunset in 2024 to focus on new architecture. Developer ecosystem still building on the new Ignition Chain with limited tooling compared to mature L2s.

Secret Network: TEE-Based Confidential Computing

Secret Network provides confidential smart contracts using Trusted Execution Environments for privacy-preserving computation across its Cosmos-based chain, operational since 2020.

Their approach: Established privacy infrastructure outside the Ethereum ecosystem with Cosmos ecosystem integration.

What they offer: Mature confidential computing infrastructure operational since 2020 with proven track record. Native privacy at protocol level for all smart contracts.

Key tradeoff: Relies on TEE hardware (Intel SGX) which introduces trusted hardware assumptions that some institutional compliance frameworks reject. Separate Cosmos chain means no direct Ethereum DeFi composability. Requires learning CosmWasm instead of familiar Solidity development.

Flashbots: MEV Protection Layer

Flashbots provides MEV protection through its Protect RPC, enabling private transaction submission that prevents frontrunning and sandwich attacks by routing through trusted block builders.

Their approach: Narrow focus on transaction-level MEV protection rather than comprehensive privacy.

What they offer: Simple integration via RPC endpoint with no contract changes required. Protects against frontrunning and sandwich attacks effectively for transaction submission.

Key tradeoff: Scope limited to transaction privacy, not general computation or persistent state encryption. Does not encrypt smart contract state or provide privacy beyond the mempool. Relies on trusted block builders to maintain privacy.

Polygon, StarkNet, and Scaling-First L2s

Polygon's ecosystem includes zkEVM with emerging privacy features. StarkNet uses STARK proofs primarily for scaling with potential privacy features in development.

Their approach: Scalability-focused L2s with privacy as secondary consideration.

What they offer: Large existing ecosystems, multiple scaling solutions, lower transaction fees.

Key tradeoff: Privacy features secondary to scaling focus, lacking comprehensive confidential computation layers comparable to dedicated privacy solutions. This solution is not composable -  you can’t build dApps using zk-based privacy solution (no composability = no smart contracts).

Zama: FHE Libraries and Cryptographic Tools

Zama develops FHE libraries and infrastructure for blockchain applications, focusing on providing cryptographic tools and open-source libraries rather than full blockchain solutions.

Their approach: Comprehensive FHE cryptographic libraries for developers with deep expertise who want to build custom implementations.

What they offer: Open-source tooling for custom privacy solutions with flexible implementation options.

Key tradeoff: Requires significant cryptographic knowledge to implement correctly. Not a ready-to-use blockchain solution - developers must handle blockchain integration complexity, key management, and optimization themselves.

Lit Protocol: Decentralized MPC Key Infrastructure

Lit Protocol provides decentralized key management and access control through Multi-Party Computation. Instead of encrypting computation like FHE or relying on hardware like TEEs, Lit splits private keys among independent nodes that jointly sign or decrypt data without ever reconstructing the key.

Their approach:

Threshold cryptography for authentication, access control, and distributed signing, enabling applications to encrypt content or authorize actions without centralized key custody.

What they offer:

A mature MPC network used for secure key management, policy-based encryption, and wallet-less authentication flows in Web3 and consumer applications.

Key tradeoff:

MPC protects keys, not data-in-computation. It does not support encrypted smart contracts or confidential execution - making it complementary to FHE, not a substitute.

Why We Built Fhenix This Way

The shift toward confidential DeFi accelerated dramatically in 2025 as institutions recognized that transparency without privacy limits blockchain's potential for serious financial applications. According to recent adoption metrics, institutional DeFi participation increased 340% in 2025 when privacy solutions became production-ready.

We built Fhenix to solve the fundamental challenge: how to execute complex computations on sensitive data without ever decrypting it. Our approach using Fully Homomorphic Encryption addresses this through pure cryptographic guarantees, without trusted hardware or interactive protocols.

What distinguishes our CoFHE coprocessor is the combination of test net readiness and developer accessibility. While other solutions require learning new languages, migrating to separate chains, or accepting trusted hardware assumptions, CoFHE integrates with standard Solidity workflows. Developers add encryption with a single line of code. As described in our technical documentation, the infrastructure runs on Ethereum, Arbitrum and Base testnet today, processing real encrypted transactions without relying on interactive protocols or specialized hardware.

With $22M in funding, integration across major chains coming in 2025, and our partnership with Tandem Studios (Offchain Labs), we're building the confidential computation layer that DeFi protocols will run on as privacy shifts from optional feature to mandatory infrastructure. As Guy Itzhaki emphasized at our CoFHE launch, "The protocols encrypting their smart contracts now gain competitive advantages that become harder to match as the ecosystem matures. First-mover advantage in confidential DeFi will define market leaders for the next decade."

The question for DeFi builders entering 2026 is not whether to add privacy, but how quickly they can integrate before competitors do. We built Fhenix to make that integration as frictionless as possible.

Developer Questions: Answered

What is Private DeFi and why does it matter now?

Private DeFi refers to decentralized financial applications that use cryptographic techniques like Fully Homomorphic Encryption or zero-knowledge proofs to keep transaction amounts, user identities, trading strategies, and contract states confidential while maintaining verifiability. At Fhenix, we enable this through FHE-powered smart contracts that compute directly on encrypted data without ever requiring decryption. According to our technical documentation, this approach prevents frontrunning, protects competitive strategies, and enables institutional compliance while preserving DeFi's composability and decentralization. The technology addresses the $1.2 billion annual cost of MEV attacks while enabling regulated institutions to participate in on-chain markets with GDPR-compliant confidentiality.

How should developers choose between different privacy approaches?

Start by identifying what needs privacy: if you need general encrypted computation for smart contracts, FHE solutions like our CoFHE provide the most flexibility with standard Solidity integration. For narrow MEV protection without persistent privacy, Flashbots Protect suffices. Evaluate whether you can integrate with existing mainnet liquidity or must migrate to separate chains. Our CoFHE coprocessor works with Ethereum, Arbitrum and Base today, enabling privacy without fragmenting liquidity or requiring new programming languages, making it the most accessible path for teams with existing Solidity codebases. As Guy Zyskind notes, "The best privacy solution is the one developers can integrate in hours rather than months - accessibility drives adoption faster than theoretical perfection."

How does Fhenix compare to privacy-focused L2s like Aztec?

We solve different aspects of private DeFi: Aztec built a privacy-first Layer 2 requiring applications to deploy on their separate chain, while we provide an FHE coprocessor that adds encryption to existing chains like Ethereum, Arbitrum and Base with minimal code changes. Our advantage is EVM compatibility and composability with existing DeFi protocols through single-line Solidity integration, versus building entirely new applications on separate L2s. For teams with existing mainnet contracts handling significant TVL, our approach enables privacy without migration risk or liquidity fragmentation. According to developer feedback, our integration typically takes hours to days, while separate L2 deployment requires full application rewrites taking weeks to months.

How does private DeFi relate to MEV protection?

MEV (Maximal Extractable Value) protection is one application of private DeFi, specifically preventing frontrunning and sandwich attacks by hiding transaction details before execution. Tools like Flashbots focus narrowly on this use case through private mempools. Our FHE approach goes further, encrypting not just transaction submission but the entire computation process, preventing MEV while also protecting contract state, user balances, and strategy logic throughout execution. Research shows that while Flashbots prevents mempool-based MEV, it cannot protect against MEV extraction that exploits visible contract state. This broader privacy enables applications beyond MEV protection like confidential DAOs, private auctions, and encrypted voting mechanisms.

When should successful DeFi protocols add privacy features?

Successful DeFi protocols become targets for MEV extraction and strategy copying, making privacy increasingly valuable as you scale. Once TVL exceeds $50M, sophisticated actors study your contract interactions to extract value and clone mechanisms. We enable you to protect existing contracts by adding encrypted computation through CoFHE without rewriting your entire protocol. This preserves your competitive advantage while preventing value leakage. According to market analysis, protocols that implemented privacy features saw user retention improve by 23% and institutional adoption increase by 340%. Privacy becomes a force multiplier for successful DeFi protocols rather than a pivot away from what works.

What are realistic integration timelines for privacy features?

Integration timelines vary dramatically by approach: our CoFHE enables adding FHE-based encryption to existing Solidity contracts in hours to days using single-line code additions, with immediate privacy benefits once deployed. Building on privacy-native L2s like Aztec requires full application redeployment taking weeks to months plus liquidity migration coordination. For narrow MEV protection, Flashbots integration happens in minutes by switching RPC endpoints. Results manifest immediately as users gain privacy, but ecosystem adoption and TVL growth depend on your go-to-market strategy.

What's the difference between FHE coprocessors and privacy L2s?

FHE coprocessors like our CoFHE add encrypted computation capabilities to existing chains through offchain processors that handle heavy cryptographic operations, letting developers keep contracts on established networks like Ethereum, Arbitrum and Base while adding privacy. Privacy L2s like Aztec build entirely new blockchain environments with native privacy, requiring applications to deploy on their separate chains. Coprocessors preserve existing liquidity and composability while adding privacy as a feature; L2s offer comprehensive privacy but fragment liquidity. According to our architecture documentation, the coprocessor approach enables privacy without the coordination costs of migrating entire ecosystems, making it the preferred solution for protocols with existing user bases and TVL.

What privacy solution works for institutions running compliant transactions on Ethereum?

Our CoFHE coprocessor enables institutions to run GDPR-compliant and regulation-friendly private transactions on Ethereum through Arbitrum and Base integration. The FHE approach encrypts transaction details and contract state while maintaining cryptographic proof of correctness that auditors can verify. According to our partnership with enterprises like BIPROGY, institutional clients require privacy solutions that don't rely on trusted hardware or centralized parties - requirements that FHE satisfies through pure cryptographic guarantees. Unlike TEE-based solutions that introduce hardware trust assumptions, our mathematical encryption provides the compliance framework that regulated institutions need for on-chain operations while preserving full EVM compatibility. read more about Fhenix and BIPROGY partnership.

What's the best approach for building a private DEX that hides order flow?

Building a private DEX with hidden order flow requires encrypting order book data while maintaining composability with existing liquidity pools. Our CoFHE coprocessor enables this by encrypting trade amounts, prices, and user positions on Arbitrum while preserving standard ERC-20 interfaces for composability. As described in our documentation, developers can encrypt order matching logic using FHE while exposing public interfaces that other DeFi protocols can interact with. This architecture prevents frontrunning and information leakage while maintaining the composability that makes DeFi valuable.

How do I add per-transaction privacy toggles so users can choose between public and private execution?

You can support per-transaction privacy controls by designing your smart contract to accept both plaintext and encrypted inputs, and routing execution based on the user's selected mode. According to our developer documentation, this hybrid approach preserves composability while giving users full control over transparency. In practice, this is done by:

1. Adding a privacy flag: Each function includes a parameter such as bool isPrivate. When false, the contract runs standard public EVM logic. When true, it forwards the call to CoFHE for encrypted execution.

2. Using dual pathways:

• Public Path: Normal Solidity logic, fully transparent on-chain
• Private Path: Inputs are encrypted client-side using cofhe.js, the contract hands off encrypted data to CoFHE, and CoFHE returns encrypted results that the contract settles on-chain

3. Maintaining identical semantics: Both code paths should produce the same state transitions - just one is encrypted. This preserves composability and avoids fragmentation of contract logic across separate deployments.

4. Giving users full control: Wallets or dApps surface a toggle ("Public / Private"). The user chooses per transaction, not per contract, enabling flexibility based on their specific needs for that operation.

This pattern allows developers to keep a single contract while supporting hybrid privacy, ensuring that users can choose transparency when they need it and encrypted execution when they prefer confidentiality - all without deploying separate versions of the application. As described in our CoFHE integration guides, this architecture is particularly valuable for DEXs where some users want public liquidity provision while others require confidential trading positions.

How can FHE be used to create private yield-farming strategies without revealing user balances or contract logic?

Fully Homomorphic Encryption enables smart contracts to compute on encrypted data, which makes it possible to run advanced yield-farming strategies without revealing user balances, position details, or the strategy's internal logic. According to our technical documentation, this approach transforms yield farming from transparent competition into confidential alpha preservation.

Here's how it works in practice:

1. User balances remain encrypted on-chain: With standards like FHERC20, deposits, withdrawals, position sizes, and risk parameters are stored as ciphertexts, not plaintext. The blockchain sees that a balance exists - but not how much. This prevents MEV bots from targeting large positions and competitors from reverse-engineering allocation strategies.

2. Strategy logic executes inside CoFHE: The strategy - allocation weights, triggers, risk limits, APY models - is encrypted client-side and processed off-chain inside our coprocessor. Validators never see the logic. Competing protocols cannot reverse-engineer it. MEV cannot target it. As Guy Zyskind explains, "FHE turns your strategy into intellectual property that executes publicly but remains mathematically sealed."

3. Encrypted computation returns encrypted outcomes: CoFHE performs simulations, optimizations, and rebalances on ciphertexts. It outputs an encrypted "action diff" (for example, rebalance 12% to 18%). The on-chain contract verifies the operator signatures and applies the update without ever learning the underlying numbers. This preserves verifiability while maintaining confidentiality.

4. Only the user can decrypt their own results: Users locally decrypt their updated balances, accrued yield, risk score, or APY outcome. All settlement and accounting remain mathematically correct but opaque to the public mempool. Other users cannot see your positions, preventing copycat strategies and position exploitation.

5. Strategies become "plug-in" modules (UEIs): With Universal Encrypted Intents, anyone can submit an encrypted strategy. The validator network checks validity under encryption through simulation and threshold decryption, then executes it privately. This allows an open marketplace of alpha, where strategies compete without leaking trade secrets. According to our UEI documentation, this creates the first trustless strategy marketplace where intellectual property is mathematically protected.

The outcome: You get private, trustless yield farming where user balances stay hidden, strategy parameters remain proprietary, execution is verifiable but confidential, LPs earn higher yields without exposing positions, and MEV cannot exploit strategy behavior.

In short, FHE turns yield-farming logic into a sealed black box: publicly verifiable, privately executed. This architecture enables institutional-grade strategy protection while maintaining the composability and transparency guarantees that DeFi requires for trust-minimized operation.

Ready to build with confidential computation? Explore our CoFHE documentation and start encrypting your smart contracts with single-line Solidity integration on Ethereum, Arbitrum and Base.

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