Privacy
Performance
Polynomial Precision

Store less. Transmit faster. Built for the AI era.

Datasent encodes your data into a compact, lossless format that cuts storage costs, eliminates raw data from your transmission layer, and lays the foundation for running AI workloads directly on compressed data — without rebuilding your pipeline.
Problem

Data infrastructure wasn’t built for the volumes you’re running today.

Storage systems, transmission pipelines, and processing layers were designed independently — each solving its own problem. For years that was fine. But as data volumes compound, the cracks between those systems turn into costs. You pay to store it, pay again to move it, and pay again to prepare it before anything useful happens.
Solution

One encoding layer. Three immediate wins.

Datasent encodes any data — tabular, sensor, time-series, images, video — into a single lossless format. The same representation delivers across your entire infrastructure stack.

Storage

Reduce data size before it hits storage — without losing a single byte.

Bandwidth

Transmit only the residual. Raw data never leaves your environment.

AI compute

Run AI workloads directly on encoded data — no costly reprocessing.
Process

How Datasent works

Step 1 — Encode

Encode your data into a shared model basis

Datasent transforms raw data into a compact, lossless representation using a pre-agreed model basis. Nothing is lost — every bit can be reconstructed exactly.
Step 2 — Transmit

Send only what the model can’t predict

Instead of moving raw data, only the residual — the unpredictable part — is transmitted. This reduces bandwidth and keeps sensitive data local.
Step 3 — Reconstruct & compute

Reconstruct or compute directly

The receiver rebuilds the exact original using the shared basis and residual — or runs AI workloads directly on the encoded data without full reconstruction.
Use Cases

Who its Built For

Business & Enterprise

Understand data opportunities that were previously out of reach.
Explore productBusiness & Enterprise

Researchers & Academics

Dive into how privacy-first computation works.
View researchResearchers & Academics

Developers

See the tech and code in action.
View on GitHubDevelopers
White Paper

The system behind Datasent

A technical breakdown of how shared model bases, residual transmission, and governed reconstruction work — and what this unlocks for storage, bandwidth, and AI compute.

Ready to keep your raw data where it belongs?

Datasent is in early access. We’re working with a small number of data infrastructure teams to validate performance and deployment configurations across real workloads.
Questions? Reach us at