Paris-based Zama, which is developing fully homomorphic encryption tech for blockchain and AI apps, raised a $57M Series B at a $1B+ valuation
With GPU scaling, chip development, and Ethereum-compatible tools, Zama is turning FHE from theoretical to practical at scale.
Context & Ripple Effects
Zama’s new financing follows its earlier $73M Series A, extending its effort to make fully homomorphic encryption usable in blockchain and AI applications. The stated emphasis on GPU scaling, chip development and Ethereum-compatible tools makes this a commercialization-focused step rather than a standalone cryptography research milestone.
The round also sits alongside prior funding for FHE-oriented hardware: Cornami raised capital for an architecture optimized for FHE, underscoring that the bottleneck spans software, compute and specialized silicon.
First-order effects
- Zama gains capital to pursue the GPU, chip and Ethereum-tooling work described in the report, while its $1B+ valuation gives it a more prominent financing position in FHE.
- Developers seeking encrypted-computation tooling for Ethereum-compatible and AI applications have a better-funded prospective platform supplier.
Second-order effects
- FHE infrastructure rivals, including hardware-focused players, face greater pressure to demonstrate practical performance and developer usability rather than cryptographic promise alone.
- The combination of GPU scaling and chip development makes the relevant competitive arena broader: software tooling, accelerator design and blockchain integration must work together for deployment.
Third-order effects
- If FHE platforms can repeatedly translate research into usable developer tools, privacy-preserving computation could become an infrastructure layer across AI and blockchain rather than a niche cryptography specialty.
- Capital may increasingly favor teams that control multiple parts of the encrypted-compute stack—software, hardware optimization and ecosystem integrations—though real-world performance remains the key constraint.
The trend: The funding is one data point in the commercialization of privacy-preserving compute, where cryptography startups are pairing specialized hardware work with developer-facing AI and blockchain tooling.