The questions
before the roadmap.
Applied research, proof-of-concepts, and experimental R&D where software engineering meets AI, for companies and academic partners.
Proof-of-concepts, applied research, and university partnerships at the AI/SE intersection.
Some ideas are too new for a roadmap. Nobody can tell you yet whether it works, what it costs, or where the limits are. That is the point of finding out.
We run R&D the way engineers should: a sharp question, a time-boxed experiment, a working prototype, and a written answer, including when the answer is no.
For academic partners, we support applied work end to end: experiment infrastructure, reproducible pipelines, and engineering rigour behind the paper.
What we actually do.
- 01Feasibility studies
Time-boxed investigations that end in a clear answer: works, doesn't, or works-if.
- 02Prototypes & proof-of-concepts
Working software that tests the risky assumption first, not the easy ones.
- 03Applied & academic research
Experiment design, reproducible pipelines, and co-authored publications where it fits.
- 04Research tooling & infra
The machinery that makes research repeatable: data pipelines, eval harnesses, compute orchestration.
A vague ambition becomes a testable hypothesis with a budget and a deadline.
Short cycles, honest measurements, findings reported as they land.
A working prototype and a written recommendation: invest, pivot, or stop.
- Quarterly report
- Working prototypes
- Co-authored papers (optional)
- Tooling + infra
We’ll tell you straight.
- Questions where being wrong cheaply beats guessing expensively
- Teams exploring the edge of what AI can do
- Universities and labs that need engineering depth
- Deadlines that need certainty. Research promises answers, not outcomes.
R&D de-risks the novel parts of everything else we do.
Start with
research & r&d.
Book a 20-minute call. We’ll tell you honestly whether this is the right starting point — or whether another door fits your problem better.
Book a call