VECTORIOThe instrument outgrew the workstation. The queue outgrew your patience.
Instrument-scale data. Notebook-scale hardware.
Reduce, analyse and sign large scientific, satellite and imaging data close to where it is created.
What changes for you.
Instrument data on one machine
294,576 rows of pathology features in 46.2 s on a single machine (measured).
From satellite scene to map
Sentinel-2 scenes become a signed heat map on one machine.
Citable results
Same input, same output, with a hash per step — ready for the methods section.
Sensitive data stays local
Patient images and unpublished data are processed at the institute.
Real workflows. From this field.
5 workflows from our test suite that teams in this field start with — ready to adapt to your data.
100 million rows are split across two machines by key and answered by one query.
- RandomDataProviderGenerators.Random
- Cluster NodeCluster.Node
- Command Control NodeWorkflow.Streaming.CommandControlNode
- CLI ProcessorETL.CLIProcessor
src → Generators.Random
fab → Cluster.Node
q → Workflow.Streaming.CommandControlNode
out → ETL.CLIProcessorA gigapixel slide is read tile by tile, blank glass is skipped, stains are separated and texture features computed — on one machine, without uploading the image.
- Camelyon16 ReaderPyramidal TIFF
- Tissue DetectionTissue Detector
- H&E DeconvolutionColor Deconvolution
- Texture FeaturesFeature Extractor
- Feature CSV ExportCSV Publisher
wsi-read → Image.PyramidalTiff.Subscriber
tissue-detect → Health.TissueDetect
stain-deconv → Health.StainDeconv
features → Classification.Features
csv-out → CSV.PublisherRed and near-infrared bands are joined per pixel and turned into a vegetation index report.
- Red Band · NIR BandRandomDataProvider · RandomDataProvider
- Join R + NIR BandsHash Join
- Compute NDVICompute Fields
- NDVI Report CSVCSV Publisher
band-r → Generators.Random
band-nir → Generators.Random
band-join → ETL.HashJoin
ndvi-compute → ETL.Compute
ndvi-csv → CSV.PublisherA live camera stream is analysed by a local model; only confident detections are kept and sealed as evidence.
- CameraRTSP Stream Input
- Detect · MonitorONNX Classifier · Video Viewer
- Row FilterETL.Filter
- EvidenceEvidence Collector
- PackageEvidence Pack
camera-input → Video.RTSP.Subscriber
object-detect → Classification.Onnx
confidence-filter → ETL.Filter
evidence-collect → Forensic.EvidenceCollector
evidence-pack → Forensic.EvidencePack
viewer-output → Video.ViewerAn audio file runs through a chain of ten effects to the speaker in real time — the same engine at 48 kHz.
- Beethoven Input · Gain 1Audio File Input · Audio Gain
- EQ 1 · CompressorParametric EQ · Audio Compressor
- Noise Gate · ChorusAudio.Gate · Audio Chorus
- Delay · ReverbAudio Delay · Audio Reverb
- Limiter · Output GainAudio Limiter · Audio Gain
- Speaker OutputSpeaker Publisher
beethoven-in → Audio.File.Subscriber
gain-1 → Audio.Gain
eq-1 → Audio.Eq
compressor → Audio.Compressor
gate-1 → Audio.Gate
chorus-1 → Audio.Chorus
delay-1 → Audio.Delay
reverb-1 → Audio.Reverb
limiter-1 → Audio.Limiter
gain-out → Audio.Gain
speaker-output → Audio.Speaker.PublisherReal workflows and node types; the designer view is illustrated. Measured values come from our end-to-end test runs.
Find your role. 5 of them.
Research instruments & big-science data
Instrument data. Answers in minutes.
Climate, weather, geodata & earth observation
Satellite scenes to a signed city map.
Digital pathology & microscopy imaging
Slides classified. Results signed. On-prem.
Automotive & mobility test data
Test-drive logs, filtered at the garage.
Media & streaming analytics
Real-time media, no dropped frames.
Your pilot. Three steps.
Your data shape
Tell us what data you have, where it lives and what the result must be.
A scoped pilot
On your data and your hardware, with the success measure written down first.
A clear decision
You see the result against that measure — and keep every workflow and record.
Bring us your hardest data problem. Let's solve it together.
A short pilot on your data and your hardware. We agree on what success looks like before we start.