Store less.
Transmit faster. Built for the AI era.
Datasent is a lossless encoding SDK. It compresses any data, tabular, time-series, sensor, image, or video, into structured tokens. Raw records never leave your environment. Storage shrinks, bandwidth drops, and analytics and AI run on the tokens directly, without a separate decode step in front of every workload.
Problem
Data infrastructure wasn't built for the volumes you're running today.
Storage, transmission, and processing layers were designed independently. Each one solves its own problem. As volumes compound, the cracks between them turn into cost. You pay to store the data, you pay again to move it, and you pay again to prepare it before anything useful runs on it.
Conventional compression helps with the first line and breaks the next two. Compressed bytes are opaque, so analytics and AI force a full decode before any work can run. The compression and the work cancel each other out.
Conventional compression helps with the first line and breaks the next two. Compressed bytes are opaque, so analytics and AI force a full decode before any work can run. The compression and the work cancel each other out.
Solution
One encoding layer. Three immediate wins.
Datasent encodes any data, tabular, sensor, time-series, images, and video, into a single lossless token format. The same representation delivers across storage, transmission, and compute.
Storage
Compress Losslessly
Shrink data by 50 to 250x on
sensor and time-series streams. 500 to 3,000x on
video. The original is always
exactly recoverable, down to
the byte.
Shrink data by 50 to 250x on
sensor and time-series streams. 500 to 3,000x on
video. The original is always
exactly recoverable, down to
the byte.
Bandwidth
Raw data stays local
A shared model basis is agreed
once between environments.
After that, only the residual
(the unpredictable part)
crosses the network. The
original is reconstructed
exactly on the other side. Raw
data never leaves the source
environment.
A shared model basis is agreed
once between environments.
After that, only the residual
(the unpredictable part)
crosses the network. The
original is reconstructed
exactly on the other side. Raw
data never leaves the source
environment.
Analytics & AI
Skip the decode step
Tokens are sufficient statistics
for trend analysis, anomaly
detection, similarity search,
model training, and inference.
Models match raw-data
accuracy at a fraction of the
data volume, latency, and cost.
Tokens are sufficient statistics
for trend analysis, anomaly
detection, similarity search,
model training, and inference.
Models match raw-data
accuracy at a fraction of the
data volume, latency, and cost.
Process
How Datasent works
Lossless
Every byte recoverable.
Data is segmented and fitted against a deterministic basis. The unpredictable part (the residual) is stored exactly. Reconstruction is mathematically exact, not approximate. If the basis captures nothing, the residual still recovers the original at full fidelity.
Local
Raw data stays put.
Both environments agree on the basis upfront. Only the residual and a small metadata payload travel. The basis carries most of the information, is then restored on each side not transmitted. Raw records never cross a network boundary.
Limitless
Usable, not just stored.
The coefficient matrix inside each token is a sufficient statistic for trend analysis, anomaly detection, similarity search, model training, and inference. Analytics and AI run on the tokens directly, with no decode step in front of every workload.
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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