ZipherCode installs a lossless compression engine on your existing infrastructure — reducing storage, transmission, and compute costs without changing a single workflow. No new hardware. No risk. Just smaller data and faster AI.
ZipherCode provides the software, handles the installation, and guarantees measurable results — all at zero upfront cost. We only make money when you save money. That's the model.
Get started →Less data stored and delivered, depending on your file mix and data type.
Every file decompresses to an exact copy of the original. Zero data loss, guaranteed.
Compression runs silently in the background. Your team notices nothing — except lower bills.
No licensing fees, no hardware spend, no risk. We install and you pay only from verified savings.
Each platform solves a different dimension of the infrastructure cost problem — and they're built to work together. Deploy one, or both.
More reduction than Zstd, BZip, 7-Zip, JPEG XL, and JPEG 2000 — across every benchmark category.
Our engine uses neural networks and recursive passes to find patterns conventional algorithms miss — while guaranteeing bit-for-bit exact restoration every time. It installs on your existing storage infrastructure and runs entirely in the background.
Learn how it works →More AI throughput from the GPUs you already own — at a fraction of what you'd spend on additional hardware.
ZipherCode unlocks underused capacity inside your existing GPUs — including Tensor Cores — and distributes compression workloads across parallel compute. The result: faster inference, lower GPU costs, and no new hardware required.
Learn how it works →Most infrastructure cost problems are solved by buying more hardware. ZipherCode solves them by making your current hardware do more — invisibly, continuously, and verifiably.
Installs on your current systems. No new hardware, no infrastructure changes, no migration. Both platforms deploy as a software layer on your existing storage and compute.
Runs completely transparently. Compression and decompression happen in the background with minimal latency. Your team and your applications work exactly as before.
Every saving is verified. We measure storage eliminated and throughput gained on an ongoing basis. You always know exactly what ZipherCode is delivering.
Works at any scale. From edge devices to multi-petabyte data centers — the same advantage applies wherever storage, compute, or bandwidth is a constraint.
If you're managing more than a petabyte — or running AI inference at scale — ZipherCode can reduce what you spend on storage, bandwidth, and compute without changing your infrastructure.
Run more inference on the hardware you have.
GPU Acceleration unlocks Tensor Core capacity inside your existing GPUs — delivering ~2× more AI throughput without adding a single card.
Stop buying storage. Start compressing it.
Lossless compression works invisibly across your file environment — targeting ≈50% lower storage costs with no change to how your teams work.
More capacity from the rack you already own.
Deploy compression across storage infrastructure to hold dramatically more data on existing hardware — reducing both your footprint and your energy bill.
Compress the cost of storing and serving media.
High-resolution image and video files compress significantly — reducing storage, CDN egress, and delivery costs across large content libraries.
We start with a scoped pilot on your actual infrastructure — so you see real numbers before committing to anything. Let's talk about what that looks like for your environment.
