In an era where data breaches, surveillance, and on-chain transparency expose sensitive information daily, true privacy online remains elusive. Traditional encryption protects data at rest or in transit, but once computation begins, decryption is required—leaving information vulnerable to servers, hackers, or intermediaries. Enter Fully Homomorphic Encryption (FHE), a groundbreaking cryptographic breakthrough that allows computations on encrypted data without ever decrypting it. And leading the charge to make FHE practical and accessible is Zama, an open-source cryptography company transforming this once-theoretical technology into real-world solutions for blockchain, AI, and beyond.

What is Fully Homomorphic Encryption?

Fully Homomorphic Encryption, first conceptualized by Craig Gentry in 2009, enables arbitrary computations (addition, multiplication, and more complex operations) directly on ciphertext. The result remains encrypted, and only the holder of the private key can decrypt the output. This "holy grail" of cryptography preserves end-to-end privacy during processing, unlike partial homomorphic schemes or trusted execution environments that rely on hardware assumptions.Zama builds primarily on the TFHE (Threshold Fully Homomorphic Encryption) scheme, which excels at Boolean and integer operations over encrypted data. By optimizing algorithms, parameters, and hardware usage, Zama has turned slow, impractical FHE into something scalable and developer-friendly.

Zama: From Vision to Unicorn Status

Founded in 2020 by CEO Dr. Rand Hindi and CTO Dr. Pascal Paillier—a renowned cryptographer with decades of contributions to FHE and related fields—Zama has assembled the world's largest team dedicated to homomorphic encryption. The Paris-based company operates as an open-source pioneer, releasing tools freely to accelerate adoption.Zama's journey includes major milestones:

• Raising significant funding, including a $73 million Series A in 2024 (valuing the company near $400 million) and a $57 million Series B in 2025, achieving unicorn status (over $1 billion valuation).
• Total funding exceeding $150 million, backed by investors like Pantera Capital, Multicoin Capital, Protocol Labs, and others.
• Launching the Zama Confidential Blockchain Protocol, with mainnet on Ethereum in late 2025 and plans for broader EVM chains and Solana in 2026.

Zama's mission is clear: make privacy the default, not an afterthought. As Rand Hindi has emphasized, privacy should be effortless—users shouldn't need to worry about it because the technology handles it seamlessly.

Core Technologies and Tools

Zama's ecosystem revolves around several key open-source libraries:

• Concrete — A compiler that converts Python (or other) programs into FHE equivalents, handling noise management, parameter selection, and optimization automatically. Developers write normal code; Concrete transforms it for encrypted execution.
• Concrete ML — A privacy-preserving machine learning framework built on Concrete, supporting scikit-learn-style models, PyTorch via ONNX, and more. It enables encrypted AI inference—ideal for healthcare (analyzing patient data without exposure) or confidential analytics.
• TFHE-rs — A pure Rust implementation for Boolean and integer arithmetic on encrypted data, emphasizing performance and security.
• fhEVM (Fully Homomorphic Ethereum Virtual Machine) — A specialized runtime allowing confidential smart contracts on Ethereum-compatible chains. Data stays encrypted during on-chain processing, enabling private transactions, balances, and logic.

These tools abstract cryptography complexity, letting developers build without deep expertise in the field.

Applications and Use Cases

Zama's FHE unlocks powerful applications:

• Blockchain and DeFi — Confidential token swaps, lending, yield farming, private stablecoins (e.g., cUSDT transfers demonstrated on mainnet), and self-custodial banking—all with full on-chain privacy while maintaining composability and verifiability.
• AI and Machine Learning — Run models on encrypted data for privacy-preserving inference in sensitive domains like medical diagnostics or financial fraud detection.
• Regulated Industries — Compliance-friendly confidentiality (e.g., selective decryption for auditors) in finance, healthcare, and defense.
• Broader Computing — Secure cloud processing, multiplayer privacy-preserving apps, and protection against quantum threats (as FHE can be made post-quantum resistant).

Partnerships, such as with Shibarium for native integration in 2026 and AWS for high-performance computing, highlight growing ecosystem momentum. Throughput has improved dramatically—from fractions of TPS to 20+ TPS on CPU, targeting 500–1,000 TPS with GPUs and dedicated ASICs.

Challenges and the Road Ahead

FHE remains computationally intensive, with operations taking longer than plaintext equivalents. Zama addresses this via coprocessors, hardware acceleration, and optimizations, making it viable for blockchain (where transaction speeds are inherently slower) first. As hardware evolves—GPUs in 2026 and specialized chips—the technology will scale further.Zama's open-source ethos invites global contributions through bounties and community resources, fostering innovation across AI, Web3, and cloud.

Conclusion

In the digital age, where data is the new oil, privacy is the ultimate safeguard. Zama is pioneering this future by turning Fully Homomorphic Encryption from a cryptographic curiosity into practical infrastructure. With its open-source tools, massive research team, and rapid progress toward scalable confidential blockchains, Zama isn't just building technology—it's redefining what's possible when privacy becomes programmable and effortless.As adoption grows—from Ethereum mainnet deployments to integrations across chains—the promise of a truly private internet draws closer. Zama stands at the forefront, proving that in the battle for data sovereignty, encryption can win without compromise.