Product
Lossless encoding where raw data never leaves your environment.
A lightweight SDK that runs in your cloud, on your servers, or at the edge. It encodes any data into a structured lossless token format. One primitive handles tabular, time-series, images, video, audio, sensor, embeddings, and graphs. The same tokens drive your storage layer, your transmission layer, and your analytics and AI workloads. Raw data stays where it lives. The original is always exactly recoverable.
Approach
How Datasent enables this use case
Encode
Agree on the model.
Sender and receiver establish a shared basis upfront. Data is encoded against this basis, capturing its structure while isolating what cannot be predicted.
Transmit
Only the residual moves
Raw data stays in place. Only the residual which is the unpredictable part, and minimal metadata are transmitted across systems.
Reconstruct
Exact reconstruction
The receiver regenerates the basis locally and reconstructs the exact original when authorised. No exposure during transfer.
Advantage
A simpler alternative to moving data
Most systems assume data has to move, then add layers to protect it via encryption, duplication, and controlled environments. Each layer adds cost, latency, and operational overhead.
Classical compression
Reduces storage but produces opaque byte streams. Any computation requires full decompression. Raw data still traverses the network. No structural information preserved.
Columnar storage formats
Preserve schema but apply fixed heuristics, run-length, and delta encoding without adaptive model selection. Raw data moves in full. No raw-data-local guarantee. No governed reconstruction.
Why Datasent is different
Lossless and structurally explicit. Raw data stays local architecturally, not as a policy. Governed reconstruction. Works across every major data type. One encoding layer for storage, transmission, and computation.
Real impact without added risk
Faster model training
Train on data where it already lives. No transfer delays, no preprocessing overhead.
Lower compute costs
Skip repeated decode and data preparation steps. Work directly on structured representations.
Broader data access
Use datasets that were previously restricted. Share and analyse without exposing raw records.
Industries
Real-world impact across industries
Transportation & Infrastructure
Lossless telemetry without the bandwidth cost
High-volume sensor streams from connected infrastructure, traffic systems, fleet telemetry, and environmental monitors are encoded and transmitted as residuals. Raw data stays on-site. Insights reach the cloud exactly.
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Financial Services
Governed data sharing across regulated boundaries
Time-series, transactional, and behavioral data shared as token exchanges and not raw transfers. The custodian model enforces reconstruction authorization and logs every access event.
Healthcare & Life Sciences
Analytics on sensitive data without moving it
Organisations can analyse, share, and build on data without transferring raw records. With a shared model basis and residual-only transmission, data stays in place while remaining exactly recoverable when required.
AI & ML Infrastructure
Training data that's already in the right format
Token components map directly to model input features not separate preprocessing pass. Federated training across organisations exchanges tokenised residuals, not raw datasets.
Technical depth
How Datasent compares
System
Losless
Raw data stays local
Governed reconstruction
Multi-modal
Classical compression (Huffman, LZ)
Lossy transform coding (JPEG, DCT)
Columnar storage (Parquet, ORC)
Federated learning frameworks
Secure clean rooms
Datasent
Datasent is the only system that is simultaneously lossless, keeps raw data local, supports governed reconstruction, and works across every major data type. A full technical treatment is available in the white paper.
Supported data types
Every type of data your organisation produces
Tabular
Rows and columns, integer or fixed-point. The natural starting point for most data teams.
Time-series
Sequential numeric measurements over time. Sensors, metrics, telemetry, financial data.
Images
Encoded per channel. Works with any standard image format representable as pixel values.
Video
Decomposed into keyframes, motion, and residual streams — each encoded independently and composed losslessly.
Audio
PCM audio encoded as a multi-channel time-series matrix. Preserves full waveform fidelity.
Sensor and scientific data
High-volume numeric streams from IoT devices, instruments, and measurement systems.
Embeddings
Fixed-point quantised vector matrices. Lossless encoding of ML embedding spaces.
Graphs
Node features, edge lists, and adjacency matrices encoded as independent token streams.
Text
Token ID or byte sequences encoded as integer arrays.
Integration
Fits into your existing stack. Doesn’t replace it
Datasent is an encoding layer, not a database or compute platform. It sits between your raw data and the systems that store, move, and process it – adding lossless compression, trusted transmission, and governed reconstruction without requiring you to replace anything downstream.
Storage systems
Datasent-encoded files drop into any object store, data lake, or file system. S3, GCS, Azure Blob, HDFS, local disk — the format is storage-agnostic. Your existing infrastructure handles the bytes; Datasent handles what those bytes contain.
Data pipelines
Encode at ingestion and stay encoded through your pipeline. Datasent integrates at the data loader level — your pipeline logic, orchestration, and downstream systems are unchanged. No new middleware required.
ML frameworks
Datasent-encoded datasets load directly into training pipelines. Token components map to model input features without a separate preprocessing step. Compatible with PyTorch, TensorFlow, JAX, and any framework that reads from standard data loaders.
Edge and IoT
Establish the trusted setup between the edge device and the cloud endpoint once. From that point, the device encodes and transmits only the residual. The cloud endpoint regenerates the basis locally and reconstructs exactly. Raw sensor data never crosses the network.
Cross-organisation data sharing
The custodian model allows data to be shared as governed token exchanges. One party holds residuals, the custodian holds coefficient shares. Reconstruction requires explicit authorisation from the custodian and is logged.
Security & Privacy Principles
Privacy and security, built in — not bolted on
Datasent is designed around three guarantees: raw data never leaves its environment, the original is always exactly recoverable, and reconstruction happens only under explicit control.
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