Somewhere in the Atacama, a solar plant is running right now, and it is talking constantly. Its inverters are talking. Its meters are talking. Its SCADA system is talking. Every second, thousands of small facts are being generated about how well that plant is actually doing its job — and almost none of them will ever be heard by a human being.
Quorelia exists to close that gap. But before it was a company, it was two friends who couldn't stop starting things together.
Where it started
The friendship came first
For more than ten years, Diego and Jay have been building things — together, badly, well, and occasionally brilliantly. Medical kits. Biomedical devices. An international food business. Korean fried chicken. Software. Half-finished ideas that taught them more than the ones that worked.
Most of it didn't survive contact with the real world. All of it mattered. Because somewhere in that decade of trying, a pattern started to emerge that neither of them had planned for: they kept ending up at the same intersection — the place where data, technology, and money all had to agree with each other before anything could actually get built.
The founders
Two backgrounds, one obsession
Different training. Different instincts. The same conviction, arrived at from opposite directions: technology's only job is to make complicated things simple. If it isn't doing that, it isn't finished yet.
Diego Ostertag
Spanish and Chilean — a degree in Marketing and an MBA in Finance, both from the University of Chile, and an instinct for the question that matters most in any business: will someone actually pay for this, and why.
Jae Hee Kim
Grew up shuttling between Korea and Chile, a Bachelor's in Economics, and five years spent inside the machinery of renewable energy — developing and operating solar power plants. He has since led work in biotechnology, where automated systems, big data and AI run at industrial scale.
The problem
Hiding in plain sight
Renewable energy has a data problem that looks, from the outside, like a data abundance. Solar plants and battery storage systems produce an almost absurd volume of information every day. On paper, the industry has never known more about its own assets.
But ask the people actually responsible for those assets a simple question — how is the plant really doing, right now, and what needs my attention — and the honest answer, most days, is: someone is still finding out. Buried in a spreadsheet. Reconstructed manually. Delivered a week after it would have been useful.
Having data was never the hard part. Knowing what it means, fast enough to act on it — that was the problem nobody had actually solved.
What we believe
We humanize AI
There is a version of artificial intelligence that impresses people and a version that helps them. The first one produces more: more charts, more scores, more confident-sounding output nobody asked for. The second one produces less, and means more.
We build the second one. Our job is to take something enormously complex — millions of measurements a day, from thousands of devices — and hand a person back transparent numbers and facts about their own asset: something they can read in two minutes and act on with confidence.
Precise
Every figure traceable to the measurement behind it. If the data can't support the claim, we say so.
Concise
Not everything that can be reported should be. We surface what changes a decision.
Simple
Plain language, in the reader's language, so an investor and a field technician each get what's useful to them.
Looking back
Ten years, one straight line
It's only in hindsight that the ten years stop looking scattered. The medical projects taught precision. The biomedical work taught systems thinking at scale. The food businesses taught the unglamorous discipline of actually operating something, day after day, for real customers.
None of it was wasted. It was all assembly — for a problem the two of them didn't fully recognize until they were standing right in front of it: energy, data, finance, and trust, all needing the same thing at once.
Why now
The bet we're making
We don't think the next breakthrough in renewable energy is collecting more data. We think it's making the data we already have intelligent, honest, and immediately useful to the person who needs it. That's the bet Quorelia is built on.