causal-ai
(8)
Anthony Rotio and the distance between an idea and a result
A Harvard computer scientist took a detour through beer marketing and a pizza invention. Now GrowthLoop’s co-founder and co-CEO is working on a stubborn business problem: how to make the next decision better than the last.
Julian Senoner and the factory’s unanswered question
A table-football game at ETH Zurich helped set Julian Senoner on the road from researcher to founder. At EthonAI, now branded Ethon, he is building software for the people who need to know why production goes wrong.
PhaseV asks the question a failed trial leaves behind: which patients responded?
A failed trial can conceal a useful clue. PhaseV uses causal machine learning to look for it, then helps drug developers test a better design before committing patients, time and money.
The Sponsorship That Finally Met the Spreadsheet
A company built to answer marketing's awkward question - did that expensive idea actually sell anything? Alembic is taking the question from the campaign dashboard to the executive budget meeting.
The Forecast Was Never the Problem. The Missing Machine Was.
Xfactor.io wants executives to stop admiring last quarter's dashboard and start rehearsing next quarter's decisions. Its wager is simple: revenue needs a flight simulator, not another rear-view mirror.
Dynatrace Built a $2 Billion Answer Machine for When the Cloud Breaks
Most monitoring tools tell engineers that something is wrong. Dynatrace has spent 21 years - and is betting $915 million on Arize - trying to tell them what broke, why it matters, and what to do next.
Bernhard Kratzwald Wants Factories to Answer the Hard Question: Why?
The Austrian computer scientist spent years teaching AI to cope when the world changes. Now he is applying that instinct to factory floors - where one unexplained defect can become an expensive habit.
EthonAI
EthonAI (now branded Ethon) is a Zurich-based industrial AI company, spun out of ETH Zurich in 2021, that builds a Manufacturing Analytics System for factories. Its no-code platform layers on top of existing factory data sources to detect visual defects, monitor processes and run autonomous root cause analysis, using causal AI to explain what drives production variation. Customers including Siemens, Lindt & Sprüngli, Bosch and Roche use it to cut quality losses by up to 50% and raise productivity while keeping engineers in the decision loop.