Who we are

Most digital twin projects fail on one of two ends. Either the operational read is right and nobody can turn it into something you can run a decision through, or the model is sophisticated and doesn't resemble the plant.

Jed spent a career in large-scale manufacturing and automation — the floor half: how production data actually gets recorded, why the routing master is wrong, and which numbers an operations lead will believe.

Roman comes out of computer science research on digital twins — the modeling half: what a simulation can legitimately claim, and where it quietly stops being evidence.

Between us we've seen this from both ends. Which is why the first thing we tell you is what your data can't answer.

What we won't do

We won't hand you a number without telling you what it rests on.

Every model runs on some mix of measured facts and assumptions, and once those are blended, a guess is indistinguishable from evidence.

So before we show you a single result, we tell you what your data can answer, what it can't, and which file would close the gap.

Sometimes the honest answer is that your export doesn't support the question you're asking. You'll hear that from us on the first call, not after the invoice.