Independent, expertise-led consulting in forecasting, process optimization, automation, and production software, for teams who need answers they can act on.
The tools change from project to project: forecasting models, optimization, applied ML, plain software engineering. The problems they get pointed at tend to fall into one of four places.
Demand, revenue, and supply chain forecasts, plus the planning models built on top of them, engineered to hold up against real-world volatility and keep running in production, not just in a slide deck.
Turning operational data into decisions a team can act on faster, and automating the repeatable parts of getting there.
Custom machine learning and AI systems built for a specific problem, not off-the-shelf, and engineered to keep working after the project ends.
A fast, honest look at whether a new AI, ML, or automation approach is worth building at all, before a team commits real engineering budget to it.
Both figures reflect production forecasting work prior to Ratio Technologies, from automotive and mobility programs, one led solely, the other as part of a larger team. Details on request.
Every engagement is worked directly by a senior data scientist and machine learning engineer, with no handoffs to a junior team partway through. Work is remote-first, scoped around the problem rather than a fixed package, and carried through to something running in production.
This is deliberately expertise-led: the practice stays close to forecasting, applied ML, and the software engineering needed to ship it, rather than stretching into general-purpose outsourcing. If a project falls outside that, that gets said plainly, early, rather than taken on anyway.
A short first conversation is usually enough to tell whether this is a good fit.
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