What you get.
Placeholder: a few lines on how cloud, on-premises or air-gapped works and why it matters.
- Your cloud account or ours
- On-premises clusters and HPC
- Air-gapped installs
- No data leaves your control
Used for
Where cloud, on-premises or air-gapped helps.
Network telemetry
Keep every counter and probe record, not a sample.
See howCall & data records
Years of CDRs and xDRs for billing and retention.
See howBroadcast archives
Decades of programmes, smaller and still broadcast-grade.
See howVideo surveillance
Months of footage from the same recorders.
See howRadio astronomy
Telescope data that outruns any disk.
See howSecurity & SIEM logs
A year of history, not 30 days.
See howAudit & compliance logs
Seven years of records, provably unchanged.
See howDatabase backups & snapshots
Keep more restore points for the same bill.
See howUser uploads & media
Every file your customers upload, stored for less.
See howTactical edge networks
Sensor and imagery feeds over contested links.
See howSIGINT & electronic warfare
Keep the raw signal for the analyst who needs it later.
See howSonar & maritime sensors
Acoustic and radar data from ships, submarines and buoys.
See howPublic records & archives
Digitised records, kept forever for less.
See howBody-worn & evidence video
Years of evidence from every officer’s camera.
See howGeospatial & mapping agencies
National imagery and elevation data, smaller.
See howForecast distribution
Get each model run to users before the next one lands.
See howSimulation & HPC
Checkpoints and outputs that no longer fill the cluster.
See howEnvironmental monitoring
Air, water and noise networks across a whole region.
See howFeatures
More features.
Neural codecs
Codecs trained on your kind of data.
Learn moreError bounds
Set the error per variable; we guarantee it.
Learn moreScientific formats
NetCDF, GRIB, Zarr, GeoTIFF and more.
Learn moreEdge & streaming
Compress at the sensor, before the link.
Learn moreSDK & CLI
One line in Python, a command in the shell.
Learn moreWe’ll cover
- Compress run on a sample of your data
- Size, speed and error compared with what you use now
- Fitting it into your pipeline
- Deployment: cloud, on-premises or edge