The evolution of artificial intelligence is built on the continuous feeding of data. From training large language models to optimizing recommendation algorithms, data is not only the fuel but also the core asset of today’s digital economy. However, a critical paradox is emerging: as the economic value of data rises, so do the motivations and risks for attacks and leaks.
By 2025, the global market for homomorphic encryption is projected to reach $306 million, with expectations to grow to $752 million by 2032, representing a compound annual growth rate of 13.9%. Behind this growth curve lies a collective awakening across industries to the central demand for "data usability without visibility." Traditional encryption technologies protect static and in-transit data, but once data needs to be computed or analyzed, it must be decrypted into plaintext—precisely the weakest link in the security chain.
Fully Homomorphic Encryption (FHE) offers a fundamentally different approach: data can be processed while still encrypted, and the computation results are output as ciphertext, with no need for decryption at any stage. This means that data processors can "use" the data without ever "seeing" the data itself. This feature has long made FHE a "holy grail" in cryptography—a theoretically sound solution that, for decades, remained impractical due to excessive computational overhead.
Zama: Leading the Transition from FHE Theory to Industrial Application
Zama is an open-source cryptography company focused on fully homomorphic encryption. Its core vision is to build end-to-end encryption solutions for blockchain and artificial intelligence. Founded by cryptographers Dr. Pascal Paillier and Dr. Rand Hindi, Zama has, over the past several years, advanced FHE from abstract mathematical theory to practical, usable code libraries.
Zama’s product suite spans the entire technology stack, from foundational cryptographic libraries to upper-layer application frameworks: TFHE-rs is an FHE arithmetic library implemented in Rust; Concrete is an FHE compiler designed for Python developers; and fhEVM enables developers to build confidential smart contracts on EVM-compatible chains. Zama’s solutions are post-quantum secure, and computation speeds have improved more than 100-fold compared to five years ago.
On the market validation front, Zama completed the first-ever confidential ICO on Ethereum mainnet in January 2026—the Zama Public Auction. The auction used fully homomorphic encryption to protect bid privacy, with all bids submitted as ciphertext. The amounts were verifiable on-chain but not viewable. The auction concluded on January 24, 2026, raising approximately $118.5 million, with over 11,000 independent users submitting nearly 24,700 bids. The final clearing price was $0.05 per token, and demand exceeded supply by 318%. On January 24, the auction app became the highest-volume application on Ethereum, surpassing USDT and Uniswap.
In terms of funding, Zama raised a total of $130 million in two rounds from 2024 to 2025, with top investors including Multicoin Capital and Pantera Capital. After the Series B round, the company’s valuation exceeded $1 billion. In June 2026, Zama acquired the institutional token distribution platform TokenOps, bringing total funding to over $150 million.
ZAMA Token Market Performance: Data-Driven Value Discovery
ZAMA is the native utility token of the Zama protocol, with a total supply of 11 billion tokens. Its primary uses include paying for network encryption and decryption fees, staking to maintain protocol security, and participating in ecosystem governance. The token became available for claiming in early February 2026.
As of July 24, 2026, Gate market data shows ZAMA priced at $0.05022, with a 24-hour gain of 1.07%, a 7-day gain of 44.14%, and a 30-day gain of 62.16%. Over the past 90 days, ZAMA rose from a low of $0.02537 to a high of $0.05970, a 76.06% increase. The current market cap is about $122 million, ranking #268, with a 24-hour trading volume of approximately $519,400. Circulating supply stands at 2.2 billion ZAMA.
Market sentiment is currently neutral, reflecting anticipation for further ecosystem adoption of the Zama protocol—especially the real-world use of confidential DeFi and confidential assets (such as cUSDT, cUSDC, cETH).
Financial AI: Confidential Protection for Trading Data and Risk Models
The financial industry has some of the most urgent needs for data privacy. Banks, hedge funds, and market makers deploying AI models for risk assessment, trading strategy optimization, and fraud detection face a fundamental dilemma: models require vast amounts of trading data for training and inference, but exposing this data risks not only client privacy but also revealing institutional trading strategies and positions.
Zama’s FHE solution offers a clear path forward. On June 17, 2026, Zama, Morpho, and Steakhouse Financial launched the first confidential DeFi yield vault on Ethereum—Steakhouse Confidential USDC Prime Vault. This vault uses fully homomorphic encryption, enabling institutions to earn yield on encrypted USDC balances without exposing positions or transaction amounts on-chain. Users can convert standard USDC to cUSDC (confidential USDC), with encrypted balances and transfer amounts recorded on-chain, while the system remains fully verifiable and includes built-in compliance modules.
On July 24, 2026, Zama launched the Confidential RFQ protocol, now in private beta on Ethereum mainnet and scheduled for public release in September. This protocol leverages FHE to hide trade direction, size, and slippage parameters on-chain, reducing maximum extractable value (MEV) and front-running risk. It supports sealed-bid auctions for market makers and will eventually enable hidden asset types and multi-chain expansion.
At the institutional infrastructure level, Zama partnered with T-REX Network in March 2026 to integrate FHE into the T-REX Ledger, providing native privacy protection for real-world asset (RWA) tokenization. In April 2026, Zama teamed up with Dfns to launch confidential wallet infrastructure, enabling banks and asset managers to conduct compliant confidential transactions on public blockchains.
Medical AI: Usability and Invisibility of Patient Data
Medical data is arguably the most sensitive of all data types. Genomic information, electronic health records (EHR), and clinical imaging data involve patient privacy and are strictly regulated by laws worldwide. Yet, AI’s potential in disease prediction, drug development, and personalized medicine depends on deep engagement with this data.
Fully homomorphic encryption offers a technological solution to this dilemma. Multiple academic studies published in 2026 confirmed FHE’s feasibility in medical settings: researchers developed privacy-preserving polygenic risk score (PRS) schemes based on FHE, enabling disease risk calculation on encrypted genomic data with negligible loss in accuracy. Other studies proposed the MedGuard framework, combining FHE with zero-knowledge proofs (zk-SNARKs) for end-to-end secure data aggregation in medical IoT (IoMT).
In industry practice, Xiao Feng presented a forward-looking concept in an industry speech in April 2026: after medical data is encrypted via FHE and converted into tokens, anyone can compute on the data via blockchain without permission, but cannot access personal information. Hospitals thus become "token factories," and individuals can upload encrypted health check data to the blockchain, enabling data ownership and circulation while protecting privacy.
Zama’s fhEVM empowers developers to build such confidential medical applications on existing public chains—smart contracts can define who can decrypt which data, ensuring end-to-end encryption without sacrificing composability.
Web3 AI Agent: Confidential Computation of User Behavior and Wallet Data
In the Web3 ecosystem, AI Agents are emerging as the new interface for users to interact with the blockchain. From automated trading execution to personalized asset management, AI Agents need access to users’ on-chain behavior and wallet data to deliver valuable services. But the question remains: are users willing to let an AI Agent "see" all their on-chain activity?
FHE changes this dynamic. By 2026, FHE is recognized as the foundational infrastructure for "secure AI agents." Within the FHE framework, AI Agents can compute on encrypted user data—analyzing trading patterns, optimizing gas strategies, assessing risk exposure—without ever "reading" the raw data.
A practical example comes from the Web3 space: the Conclave protocol uses FHE to enable multiple AI Agents to generate consensus scores for a subjective task. Each Agent’s score is encrypted client-side, and smart contracts aggregate the scores in ciphertext, decrypting the final result only after all Agents have submitted. This mechanism ensures no single Agent can influence or view another’s score.
For wallet data protection, in July 2026, self-custody trading platform Sedona partnered with Fhenix to integrate FHE infrastructure into its Arbitrum-based system, ensuring user balances, spot positions, and AI Agent spending parameters remain encrypted throughout processing. This integration eliminates 100% reliance on trusted hardware (like TEE), shifting the security foundation from hardware trust to cryptographic trust.
FHE Industrialization Challenges and Zama’s 2026 Roadmap
Despite FHE’s vast technical potential, industrialization faces multiple challenges. First is computational efficiency: while Zama has increased FHE speeds more than 100-fold compared to five years ago, encrypted computation remains significantly slower than plaintext, potentially causing latency in complex applications. Second is developer ecosystem building: FHE programming paradigms differ substantially from traditional development, requiring extensive education and toolchain improvement.
Zama’s 2026 roadmap shows the protocol will focus on Total Value Shielded (TVS) as its core target, prioritizing confidential payments, confidential capital formation, and confidential tokenization and asset management. One of the top priorities in the coming months is enabling yield functionality for confidential assets like cUSDT—users will be able to stake cUSDT, cUSDC, and cETH in mainstream DeFi protocols such as Aave and Morpho.
For chain ecosystem expansion, Zama plans to support more EVM-compatible chains in the first half of 2026 and deploy to the Solana ecosystem in the second half, enabling cross-chain confidential assets and applications.
Conclusion
The challenge of data security in the AI era fundamentally revolves around the contradiction between data "usability" and "invisibility." Fully homomorphic encryption offers a fundamental solution—allowing data to be computed, analyzed, and trained in ciphertext, without exposing plaintext at any stage. As the leader in this field, Zama has validated the industrialization of FHE through over $150 million in funding, a $118.5 million confidential ICO, and a series of financial and institutional-grade applications.
From protecting trading data and risk models in financial AI, to safeguarding patient privacy in medical AI, to securing user behavior and wallet data in Web3 AI Agents, Zama’s FHE solution is building the infrastructure layer for next-generation intelligent applications where "data is usable but not visible." Much like HTTPS enabled the widespread adoption of the internet, FHE could well be the "encrypted HTTP" that propels blockchain and AI into large-scale commercial use.
FAQ
Q: What is the Zama (ZAMA) project?
Zama is an open-source cryptography company specializing in fully homomorphic encryption (FHE) technology, building end-to-end encryption solutions for blockchain and AI. Its core products include the TFHE-rs cryptography library, the Concrete compiler, and the fhEVM confidential smart contract framework, enabling developers to build privacy-preserving applications on existing public chains.
Q: What is the difference between Fully Homomorphic Encryption (FHE) and Zero-Knowledge Proofs (ZK)?
Zero-Knowledge Proofs (ZK) are used to prove "I know a secret" without revealing the secret itself. Fully Homomorphic Encryption (FHE) allows computations to be performed directly on encrypted data, with no need for decryption. FHE ensures the entire computation process occurs in ciphertext, so nodes never know what data is being processed.
Q: What are the main uses of the ZAMA token?
ZAMA is the native utility token of the Zama protocol, with a total supply of 11 billion tokens. Its main uses include paying for network encryption and decryption fees, staking to maintain protocol security, and participating in ecosystem governance. Tokens can also be delegated to node operators to support network security and incentive mechanisms.
Q: What are the current practical applications of Zama’s FHE technology?
Zama has launched the Confidential RFQ protocol (July 2026), which uses FHE to hide on-chain trade information and reduce MEV risk; partnered with Morpho and Steakhouse to launch the first confidential DeFi yield vault; collaborated with T-REX Network to provide a privacy layer for RWA tokenization; and teamed up with Dfns to launch confidential wallet infrastructure.
Q: What risks should investors be aware of when considering ZAMA?
Key risks include: FHE encrypted computation is still less efficient than plaintext, which may cause latency in complex applications; token price volatility; ecosystem development may fall short of expectations; and uncertainty in crypto market regulatory policies. This article does not constitute investment advice—please conduct thorough research before making decisions.
