Introducing Hyper
Video conferencing has become the backbone of modern work, yet the tools we rely on every day were designed for a different era. They bolt on features as afterthoughts, leak your data to train opaque models, and assume everyone is on a fiber connection with a top-of-the-line laptop.
We think it’s time for something better. That’s why we’re building Hyper.
What is Hyper?
Hyper is a modern video conferencing platform built from the ground up around three principles:
- Privacy by architecture — your conversations stay yours. We don’t mine meeting content, period.
- Performance without compromise — adaptive codecs, edge-first infrastructure, and a native client that won’t eat your battery.
- Intelligence that helps, not surveils — real-time transcription, translation, and summaries powered by on-device models wherever possible.
Why now?
The shift to hybrid work is permanent. The average knowledge worker now spends over 10 hours per week in video calls. Despite that, most platforms still treat video as a commodity — a pipe to push pixels through.
We believe the meeting experience itself is the product. Every millisecond of latency matters. Every UI decision shapes whether people feel present or distracted. Every privacy choice signals what a company truly values.
What’s different
End-to-end encrypted by default
Every Hyper call is end-to-end encrypted. Not as an enterprise add-on, not behind a toggle — by default, for everyone. We use the Messaging Layer Security (MLS) protocol to scale encryption to large meetings without sacrificing performance.
Adaptive performance
Hyper’s media engine continuously adapts to network conditions. Simulcast, SVC, and intelligent bandwidth allocation mean your call stays crisp even when your connection doesn’t. Our native clients leverage hardware acceleration for encoding and decoding, keeping CPU usage minimal.
AI that runs locally
Transcription and translation run on-device when your hardware supports it. When cloud processing is needed, we use isolated, stateless inference — your data is never stored, never used for training, and never shared.
What’s next
We’re currently in a closed beta with a small group of teams. Over the coming weeks, we’ll be sharing more about our architecture, our approach to privacy, and the technical decisions behind Hyper.
If you’re interested in early access, join the waitlist — we’d love to have you along for the ride.