Data Engineering
Scientific data pipelines, HPC infrastructure, and end-to-end AI/ML — from data curation to edge deployment.
We build the software that transforms raw telemetry into science-ready data products. From Level 0 processing through calibration pipelines to long-term archives, we handle the full data engineering lifecycle for space missions.
Our expertise extends to the complete AI/ML pipeline: evaluating use cases, curating training datasets, building training infrastructure, optimizing models, and deploying to edge platforms. This end-to-end capability — from data curation through inference — sets us apart.
We do not build mission control systems or ground stations. We build the software that processes, archives, and exploits the data they deliver.
Capabilities
Data Pipelines
Scientific data processing, bulk calibration, Level 0 through Level 2 processing, batch orchestration.
HPC & Infrastructure
High-performance computing, parallel processing, cloud and on-premise deployment.
AI/ML Lifecycle
Use case evaluation, data curation, training pipelines, model optimization, edge deployment.
Archiving & Access
Long-term storage, query interfaces, data distribution systems.
End-to-End ML Lifecycle
Use Case
Evaluate & scope
Data
Curate & label
Model
Train & tune
Edge
Deploy on target
Technologies
Languages
- Python
- Scala
- .NET/C#
Databases
- PostgreSQL
- Time-series DBs
ML Frameworks
- TensorFlow
- PyTorch
- YOLOX
- Quantization tools
Infrastructure
- HPC clusters
- Kubernetes
- Cloud platforms
Standards
- CCSDS
- FITS
- Domain-specific formats
Project Heritage
STIX Ground Pipeline
OperationalScientific data pipeline for the STIX instrument. Processing, calibration, archiving, and distribution to the science community.
View detailsGreen Space Logistics Tool
In DevelopmentLCA integration tool for space logistics sustainability assessment.
ASN.1 Toolchain Extension
ProductionPython and Scala backends for ASN.1/ACN code generation.
Related Services
Planning a Data System?
Whether you're building a new pipeline or scaling an existing archive — we'd like to hear about your project.