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A small studio for data and software architecture.

Stratorys works on systems that collect, move, store, and query large volumes of data. We advise when the decision is the hard part, and build when implementation is required.

We keep the scope narrow.

Most performance problems are decided early: data model, storage, query patterns, and boundaries. Those choices are easier to make before the system is large.

We favor tools that are fast, predictable, and well understood: Rust for systems work, columnar engines for analytical scale, and open formats where possible.

Three principles.

Simple by design

We remove complexity rather than manage it. Systems that are easy to understand are easy to evolve, operate, and trust.

Measured delivery

We set clear technical goals and validate decisions against production metrics, not opinions. If we cannot measure it, we do not claim it.

Reliable in production

Observability, resilience, and runbooks are part of the design from day one, so the system holds up under real load, not just demos.

How an engagement runs.

01
Understand
We learn your systems, your constraints, and what good means for you. Output is a shared problem statement.
02
Decide
We characterize the workload, evaluate options, and measure where it matters. Output is written recommendations.
03
Build
On delivery engagements we implement, refactor, and harden in short cycles, validated against production metrics.
04
Transfer
Documentation, runbooks, and knowledge encoded so your team can run and evolve the system independently.

Small by design, never short-handed.

Stratorys works with a trusted network of senior engineering partners. When a project needs more hands or deep specialist knowledge, whether functional programming, big-data platforms, or domain expertise, we bring in the right people rather than the nearest ones. You get the focus of a small team and the reach of a large one.

Let's talk architecture.

Tell us about your data and your constraints, and we will tell you where we would start.