About Quantum Encoding
Using AI to Solve AI's Problem
We're researching next-generation lossless compression while building local-first software that funds our work. Better data encoding, not bigger infrastructure.
Our Mission
The AI industry is betting trillions on infrastructure. We think there's a smarter path. What if the data itself could be smaller?
We use large language models as research tools — not products to scale infinitely. Testing compression theories. Validating formulas at scale. Exploring whether data can be encoded as continuous waveforms rather than discrete bits.
How We Work
AI as a Research Tool
We use AI to accelerate research, not as an end product. Testing thousands of compression formula variations automatically. Validating mathematical approaches at scale. The goal isn't to consume more compute — it's to eventually need less.
Waveform Encoding Research
Exploring data as continuous signals rather than discrete bits. If data can be encoded more efficiently, the infrastructure problem becomes smaller — not something to outspend.
Products Fund Research
While we work on the hard problems, we build software that embodies our values: efficient, private, local-first. Every product we ship funds continued research into next-generation data encoding.
Local-First Architecture
Your data stays on your machine. No cloud servers burning energy to store what could live locally. No subscription traps. Buy once, own forever. MIT-licensed binaries.
Rust · Tauri · Svelte
Native performance. Cross-platform. No Electron bloat. Our desktop and mobile applications are built with the same efficiency principles we're researching.
Lossless Compression Target
Compression that preserves every bit of the original data. No quality degradation. The research question: can we find encoding methods that achieve better ratios than current standards?
The Problem We're Addressing
Infrastructure Bubble
OpenAI has committed $1 trillion in infrastructure over ten years. Their annual revenue is about $13 billion. The math doesn't add up without radical efficiency improvements.
Unsustainable Scale
900,000 wafers per month required for OpenAI's Stargate project by 2029, triggering a global memory chip crisis. The industry's solution to every problem is scale.
A Different Question
Instead of asking "how do we build more data centres?" — we're asking "what if we needed fewer?" Better compression means less storage, less bandwidth, less energy.
Company Information
Quantum Encoding LTD is a software development and research company registered in England and Wales.
Registered Office
33 Oxford Street
Coalville, LE67 3GS
United Kingdom
Company Details
Company Number: 16575953
Email: info@quantumencoding.io