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Zama: Revolutionizing Data Privacy with Homomorphic Encryption

Data privacy has become a critical issue in the digital age, and Zama is at the forefront with its innovative homomorphic encryption solutions.

Co-founded by Pascal Paillier and Rand Hindi in 2020, the company aims to protect sensitive data through Fully Homomorphic Encryption (FHE), a groundbreaking technology that allows computations on encrypted data without exposure.

As businesses and industries navigate increasing privacy concerns, Zama’s encryption solutions transform data usage in sectors like artificial intelligence (AI), cloud computing, healthcare, and finance.

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📸: Zama

A Visionary Start in Data Privacy

The inspiration behind Zama arose from the urgent need to balance data privacy with functionality in an increasingly data-driven world.

“Zama was born out of a desire to solve the paradox of enabling secure data usage without compromising privacy,” shares Jeremy Bradley, Zama’s COO.

This vision has evolved from a research-focused concept to a fully accessible and user-friendly encryption platform, making significant strides in deploying advanced cryptographic solutions that promise to revolutionize industries reliant on big data.

The Core Technology: Fully Homomorphic Encryption (FHE)

At the heart of Zama’s innovation lies homomorphic encryption, a transformative advancement in the encryption landscape. Traditional encryption methods require data to be decrypted for processing, which exposes it to security risks. “FHE allows data to remain encrypted during computations,” explains Bradley. This capability is vital for sectors such as healthcare and finance, where secure data processing is paramount. Their technology ensures privacy while maintaining high performance, providing practical solutions to real-world challenges. “We’ve optimized our cryptographic algorithms to ensure our solutions are both secure and efficient,” Bradley notes.

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📸: Zama

Zama’s Competitive Edge in Encryption

What sets Zama apart from other encryption providers is its commitment to usability and performance. While many competitors focus on theoretical advancements, Zama is dedicated to making homomorphic encryption accessible to developers without requiring extensive cryptographic knowledge. “We emphasize open-source tools, making our technology widely available for innovation and collaboration,” Bradley states. This approach cultivates a community-driven ecosystem where privacy-preserving applications can flourish.

Overcoming Challenges in Cryptographic Solutions

Developing cryptographic solutions presents numerous challenges, and Zama has faced its share. “Balancing security with performance has been one of our biggest challenges,” admits Bradley. FHE is inherently computationally intensive, but the company has made significant strides in refining the technology to ensure it’s practical for everyday use. Collaborations with the cryptographic research community have been essential in overcoming these challenges and pushing the possible boundaries.

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📸: Zama

Expanding Impact Across Industries and Use Cases

Zama envisions a future where FHE is a foundational technology across various sectors. In finance, FHE enables secure data analysis without exposing sensitive information. In healthcare, it allows patient data to be processed securely while adhering to privacy regulations. Governments can also benefit from FHE, ensuring secure data sharing across departments. “We see homomorphic encryption as the bedrock of privacy-preserving innovation,” Bradley emphasizes, highlighting their long-term vision.

Zama’s Flagship Product: Concrete

In its mission to democratize homomorphic encryption, Zama recently launched Concrete. This is an open-source encryption library designed for efficiency and ease of use. “Concrete allows developers to integrate FHE into their applications without needing to be cryptography experts,” says Bradley. The product will significantly impact the industry by enabling more developers to create secure, privacy-preserving applications.

Looking Ahead: Zama’s Strategic Goals

Looking to the future, Zama’s strategic goals are clear: to expand the adoption of homomorphic encryption across industries and continue optimizing its solutions. “We’re focused on building a robust ecosystem of developers and partners around our open-source tools,” Bradley shares. By fostering innovation and staying at the forefront of encryption research, Zama is positioned to shape the future of data privacy.

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📸: Zama

Zama’s journey exemplifies the power of visionary leadership and groundbreaking technology. With a focus on practicality, performance, and privacy, Zama is setting new standards for encryption in the digital age. “We’re committed to protecting privacy without compromising functionality,” Bradley emphasizes — a promise that solidifies Zama’s status as a leader in secure data processing.

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Fundraising 4 hours ago

London-based AI laboratory Ineffable Intelligence has emerged from stealth with a $1.1 billion seed round at a $5.1 billion post-money valuation, the company confirmed on 27 April 2026. The financing is the largest seed round ever raised by a European company and one of the largest first-money-in rounds in the global history of artificial intelligence. The round was co-led by Sequoia Capital and Lightspeed Venture Partners. Participating investors included Nvidia, DST Global, Index Ventures, Google, and the UK Sovereign AI Fund, the British government’s recently established vehicle for backing strategic AI capacity on home soil. A bet on a different path to general intelligence Ineffable Intelligence was founded in 2025 by David Silver, the former Vice President of Reinforcement Learning at Google DeepMind and the principal architect of AlphaGo, AlphaZero and AlphaStar. He is joined by three further DeepMind alumni: Wojciech Czarnecki, Lasse Espeholt and Junhyuk Oh. All four have spent the past decade at the frontier of reinforcement learning research, the discipline behind some of the most consequential demonstrations of machine learning over the past ten years. The company describes its objective as building a “superlearner” — an AI system capable of acquiring knowledge directly from its own experience rather than from human-generated text or imagery. “Our mission is to make first contact with superintelligence,” Silver said in a statement accompanying the launch. “We are creating a superlearner that discovers all knowledge from its own experience, from elementary motor skills through to profound intellectual breakthroughs.” The framing is a deliberate departure from the dominant industry trajectory. Most leading AI laboratories, including OpenAI, Anthropic and Google DeepMind itself, have built large language models trained primarily on the corpus of the internet, then refined that training with human feedback. Ineffable’s wager is that the marginal returns on scaling text-based pretraining are diminishing and that the next leap in capability will come from agents that learn endlessly from the consequences of their own actions, in much the same way AlphaZero learnt the game of Go without studying any human matches. Why $1.1 billion at seed The size of the round is unusual even by the inflated standards of the 2026 AI capital cycle. Two factors appear to explain it. First, frontier reinforcement learning at the scale Ineffable describes is computationally extraordinarily expensive: the company will need to operate vast simulation environments and train very large models against them, an undertaking that consumes capital at a rate closer to physical R&D than to traditional software. Second, the round signals a strategic move by Europe’s investor and policy ecosystems to retain the most ambitious AI researchers on the continent. The presence of the UK Sovereign AI Fund alongside Sequoia, Lightspeed and Nvidia is the clearest expression of that intent. The British government has publicly framed the investment as a bet on breakthrough AI that “can discover new knowledge”, positioning the country as a willing co-investor in domestic frontier laboratories. For Ineffable, the implication is access not only to capital but to compute, regulatory engagement and the still-resilient academic talent base around UCL, Oxford, Cambridge and Imperial. Founder pledge of historic scale Alongside the funding announcement, Silver disclosed that he is committing 100 per cent of any personal proceeds from his Ineffable equity to charity via the Founders Pledge network — described by the organisation as the largest pledge in its history. At the round’s $5.1 billion valuation, that commitment could ultimately exceed several billion dollars if the company succeeds. It is a meaningful gesture in a sector where the reputational stakes around concentrated AI wealth are escalating, and one likely to be referenced in subsequent founder-led commitments. Implications for the European AI landscape Ineffable’s emergence reshapes the European AI map in three concrete ways. It establishes London as the home of the continent’s largest-ever seed-stage company, complicating Paris’s recent narrative of frontier-AI primacy after Mistral’s earlier rounds. It validates a thesis — that reinforcement learning, not transformer scaling, is the next frontier — that has lately been losing capital share to language-model incumbents. And it confirms that the UK government is now willing to act as a balance-sheet co-investor in domestic AI laboratories, a posture much closer to the French model than to the predominantly grant-based regimes elsewhere in Europe. The execution risk is non-trivial. Reinforcement learning at frontier scale has historically required years of careful environment design before producing competitive systems, and Ineffable’s “first contact” framing sets a high bar against which it will be judged. But for now, with a billion dollars on the balance sheet, four of the discipline’s most accomplished researchers in the founding team and a sovereign co-investor at its back, Ineffable Intelligence is the most heavily resourced new entrant in the European AI cycle. Sesamers covers European fundraising rounds across deeptech, fintech and AI. Source: tech.eu.

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