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, with 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 including tabular, sensor, time-series, images, and video, into a single lossless format. The same representation delivers across your entire infrastructure stack.
Storage
Your data takes up less space, with nothing left out. Lower storage bills, zero compromise.
Bandwidth
Raw data stays where it is. The
receiver reconstructs the exact
original from the shared basis
plus what arrived.
receiver reconstructs the exact
original from the shared basis
plus what arrived.
AI compute
AI workloads can operate
directly on your compressed
data, no costly re-processing.
The savings compound as your
AI usage grows.
directly on your compressed
data, no costly re-processing.
The savings compound as your
AI usage grows.
Process
How Datasent works
Step 1 — Encode
Data is encoded against a
shared model basis
The sender fits canonical data
against the agreed basis and
computes the residual, which is
the exact integer difference
between what the model
predicted and what the data
actually is. For well-structured
data, the residual is small.
against the agreed basis and
computes the residual, which is
the exact integer difference
between what the model
predicted and what the data
actually is. For well-structured
data, the residual is small.
Step 2 — Transmit
Only the residual crosses
the wire
Residuals flow to storage,
analytics tools, AI models, and
partners via a consistent token
format. Raw data never leaves
the sender's environment. The
basis stays local on both sides.
analytics tools, AI models, and
partners via a consistent token
format. Raw data never leaves
the sender's environment. The
basis stays local on both sides.
Step 3 — Reconstruct & compute
The receiver rebuilds the
exact original
The receiver regenerates the
basis locally from the trusted
setup parameters, combines it
with the arrived residual, and
reconstructs the exact original.
Reconstruction can be gated
by a custodian.
basis locally from the trusted
setup parameters, combines it
with the arrived residual, and
reconstructs the exact original.
Reconstruction can be gated
by a custodian.
Use Cases
Who it's Built For
Business & Enterprise
Understand data opportunities that were previously out of reach.
Explore product
White Paper
Deep dive into Datasent's approach
The white paper covers the full mathematical framework: lossless tokenization, adaptive
segmentation, token-space computation, and zero-knowledge proof compatibility. No proprietary
dependencies. No lossy trade-offs.
segmentation, token-space computation, and zero-knowledge proof compatibility. No proprietary
dependencies. No lossy trade-offs.
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 info@datasent.com
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