Research and experimental software engineering
Feasibility studies, prototypes, measurement processing and low-level optimisation. We answer “will it work?” before you commit to full-scale development.
When you need R&D
R&D is needed when there is no ready answer: it is unclear whether accuracy, performance or data will be enough, and choosing the wrong approach would be expensive.
Find out whether the task can be solved on your data
Compare technologies and approaches under real constraints
Process measurement and equipment data
Speed up computation in C, C++ or Rust
Write software around existing equipment: protocols, drivers, integrations
Build a prototype before industrial development
Selected work
HarvesterLib
A C++20 library for timber harvester measurements: parsing and validation, alignment to a regular grid and extrapolation.
How a study runs
Question and criteria
We state a testable hypothesis, metrics and success criteria.
Data and environment
We collect representative data and a test setup with the equipment’s real constraints.
Experiments
We start from a simple baseline and compare approaches measurably.
Prototype
We build the smallest system that can prove the solution.
Conclusion
You receive the code, measurements, rejected approaches and a recommended next step.
What you get
A justified decision: build it, how to build it, or don’t. A negative result saves money too.
A technical report with measurements
Prototype code
A comparison of the approaches considered
The risks and limits of the solution
A recommendation for the next stage
Questions
Do you guarantee the outcome of a study?
We guarantee an honest answer, not a target accuracy: a study may show that an approach does not work, and that is a result too.
Do you design electronics?
No. We are responsible for the software and the data; the client provides the equipment, access to it and its technical documentation.
What happens after the prototype?
If the solution holds, we move to industrial development at NDDev.Dev or hand the result over to your team.
What do you write in?
Computational and low-level parts in C, C++ and Rust; analysis tools are chosen for the task.
Tell us about your hypothesis
Describe the task, the data and the equipment — we will suggest how to test the idea quickly and measurably.