Loved this tutorial and am working through it!

Surprisingly fewer than you might think

this was so much fun to film!

Excited to announce that Sunscreen is being acquired by @fhenix! We’ve spent 4+ years building at the frontier of applied cryptography. As we got to know the Fhenix team over the last year, it’s become clear they’ve built a powerhouse team (@GuyZys, @GuyItz, @ChrisPeikert, @l_woetzel, @laurenmxv to name just a few) best positioned to bring production-grade FHE to the world. Our mission continues at Fhenix, and our work remains open-source under the AGPL license. We’re deeply grateful for all the support from the community, our investors, and our friends through these years, especially NuCypher/@TheTNetwork for serving as our very first believers. If you’re working on cryptography, privacy-preserving systems, or ambitious infrastructure more broadly, I’d love to connect. - Ravital, on behalf of Team Sunscreen

Private internet voting has always had a hard constraint: How do you verify the tally without exposing the votes? In our latest post, we unpack why truly private voting remains elusive, and how ZKPs, threshold cryptography, and FHE get us closer. blog.sunscreen.tech/why-trul…

Private information retrieval is the Trojan Horse of homomorphic encryption. It's already deployed to hundreds of millions of users by Apple and Meta. We broke down how it works and built a private DNS demo to show it in action: blog.sunscreen.tech/private-…

FHE

The Achilles’ heel of software is its need to decrypt data for processing. FHE eliminates that window of exposure, enabling what some call “full-privacy computing." We are loving reading this from @barisozmen_twi Read: bozmen.io/fhe

FHE vs TEEs Read more: medium.com/@trekeptor/tee-vs…

We're excited to announce our partnership with @latticaai to bring production-ready TFHE to developers. Our Parasol compiler helps builders turn ordinary code into high‑performance FHE programs. With Lattica's managed infrastructure, you can deploy encrypted computation without spinning up your own servers. What this means: compile locally with Sunscreen, deploy to Lattica, and run programs on encrypted data in production. No plaintext exposure, no infrastructure headaches. This opens the door for applications requiring exact computation on sensitive data - from smart contracts to secure voting to genomic analysis. Get started with 3 free compute hours: lattica.ai/tfhe Read more on our blog: blog.sunscreen.tech/deployin…

Both TEEs and FHE enable privacy-preserving computation, but they approach the problem from different angles. If performance is critical and trust in hardware is acceptable → TEE is a practical choice. If absolute data privacy and decentralization matter most → FHE is the holy grail.

FHE lets you compute directly on encrypted data, without needing to decrypt data at all. Benefits: 1/ Trust in math; cryptographic guarantees 2/ Good for cloud or decentralized systems where zero trust is important 3/ When data is never decrypted, the attack surface is reduced significantly. Disadvantages: 1/ Currently slower than TEEs for many commercial use cases (but improving fast) 2/ Dev effort can be slightly higher.

Private compute isn't just one thing, it's a spectrum of a trust model. TEEs trust hardware, FHE trusts math. Regardless of whether you're building an AI or blockchain app, you should ask: what (or who) are you trusting and whether that trust assumption works for your app.

Builders shouldn't have to rebuild their application or learn a new programming language to integrate privacy. Ship private apps with FHE while keeping your stack, and without changing a thing.

Read our paper on Parasol and CBS-cmux below. Accepted to IEEE S&P 2026 (Oakland). eprint.iacr.org/2025/1144.pd…

Excited to share that Parasol, our FHE compiler encompassing a virtual processor with a custom ISA and a low-level library for FHE ops already supports circuit construction using CBS-cmux. Learn more here:

Introducing Circuit Bootstrapping (CBS) - cmux A purpose-built, and novel encrypted computing environment, based on Circuit Bootstrapping, that significantly reduces latency and increases parallelism in FHE operations.

yep with fhe