Services
What we build with R
Internal Tools and Data Interfaces
We build internal tools that sit directly on top of your data: editable tables, dashboards, admin panels, and operational interfaces.
These tools are server-driven, fast, and designed for real workflows rather than demos. Pagination, search, validation, and concurrency are handled on the server to keep behavior predictable.
Used when spreadsheets stop scaling and more efficient tools are required.
Data Pipelines and Processing
We build data pipelines for ingestion, transformation, and delivery. These systems handle data at rest and data in motion: files, streams, scheduled jobs, and event-driven workflows.
We focus on correctness, traceability, and failure handling: late data, retries, partial writes, and auditability are first-class concerns. R provides a consistent foundation for both data processing and the services around it.
Used when data needs to move safely through multiple stages.
Backend and API Systems
We design and build backend services that move data reliably between systems. This includes HTTP APIs, background services, and internal platforms where correctness, performance, and observability matter.
Typical work includes request handling, validation, persistence, structured logging, and clean interfaces between components. We favor simple, explicit designs over framework-heavy abstractions.
Used when you need stable systems that other systems depend on.