What we do
Consulting built around your requirements, from translating R&D methods into production pipelines to reviewing and redesigning existing systems.
- 01
Pipeline and backend architecture
Starting from your requirements, review how data moves from raw imagery to finished product, and the backend that runs and serves it. Find the bottlenecks and design a system that fits your volumes, deadlines and budget.
- Review and redesign of existing systems
- Orchestration, storage and data model design
- Cloud, on-premise or hybrid
- 02
From R&D to production
Taking the methodology your R&D team has validated in a proof of concept and translating it into a production system: a data pipeline built for production throughput, with the backend to run it and deliver its results.
- Working directly from your R&D team’s methodology
- Translating prototypes into production pipelines
- APIs and services to run the pipeline and deliver results
- 03
Migration to the cloud
Moving pipelines and the services around them from fixed, pre-allocated infrastructure to scalable pay-as-you-use services. In a recent project, processing ten years of data for one area of interest fell from over two hours to about five minutes.
- Bare metal to cloud-native services
- Elastic scaling for peaks and backlogs
- Lower running costs through pay-as-you-use
- 04
Geospatial processing at scale
Workflows built around the demands of geospatial data: many areas of interest in parallel, long historical time series and large imagery archives, processed quickly and accurately, with the results stored and served to your products.
- Many areas of interest in parallel
- Long historical time series
- Results stored for fast queries and delivery