Expansion Vertical

Where We're Headed

Geospatial

Spatial platforms are only as reliable as the infrastructure running them. We're bringing managed DevOps to GIS, remote sensing, and location intelligence systems that need to stay online.

What We're Built For

Managed infrastructure and DevOps services designed for geospatial platforms.

Platform Infrastructure

Provisioning and managing the servers running your GIS platform, tile servers, spatial APIs, and data processing pipelines.

Uptime & Monitoring

24/7 observability stacks watching spatial service health — tile rendering latency, API error rates, and database query performance surfaced before users notice.

Deployment Pipelines

CI/CD automation for geospatial platforms — controlled releases to production without manual deployments, environment drift, or data processing interruptions.

Data Backup & Recovery

Automated backup procedures for spatial databases, raster stores, and processed datasets — with tested restore procedures, not assumed ones.

Cost-Optimised Hosting

Hetzner and bare-metal options for storage-heavy geospatial workloads — significant savings over cloud-native defaults for data that doesn't need to live in AWS S3.

Kubernetes Operations

Orchestrating geospatial processing workloads and API services in containerised environments — scalable, reproducible, and managed day-to-day.

The Gaps We're Designed to Find

Common infrastructure problems in geospatial platforms — and how we approach them.

01

GIS Platform With No Monitoring

A tile server or spatial API running with no visibility into request latency, error rates, or disk saturation — the first sign of a problem is a client reporting a blank map.

Monitoring
02

Unstructured Data Environments

Rasters, vector datasets, and processing outputs scattered across local drives and shared folders — no version control, no access management, no recovery path if a drive fails.

Resilience
03

Manual Processing Pipelines

Imagery processing and data preparation workflows run manually by a single analyst — no automation, no reproducibility, and a full block if that person is unavailable.

Automation
04

Cloud Storage Costs Scaling With Data Volume

Spatial datasets growing month over month in cloud object storage priced for the enterprise — when the actual use case calls for a well-managed dedicated server at a fraction of the cost.

Cost

Expansion vertical: Geospatial is where we're headed, not where we've been. If you're running a spatial platform, GIS service, or location-intelligence system with an infrastructure problem, we'd like to hear from you.

Running a spatial platform?

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