How Novarum Scholar came to be

I'm a limnologist. I study the biogeochemical cycles of freshwater systems, using drone technology and AI to understand how lakes and rivers process nutrients, carbon, and matter at a scale that wasn't possible a decade ago. It's a field that moves fast, borrows methods from adjacent disciplines, and publishes constantly.

Before I even started my PhD, I had already developed a habit I suspect most researchers recognize: doom-searching. Open a browser to write. End up in Google Scholar forty minutes later, three pages deep into tangentially related papers, with seventeen tabs open and nothing written. Not because I wasn't working. Because keeping up with the literature felt like a job in itself.

The alerts I set up weren't helping. They were noisy, inconsistent, and easy to ignore. I'd let them pile up, batch-delete them, and tell myself I'd do a proper sweep later. I never did.

Then I heard a story that I couldn't stop thinking about.

A friend told me about a PhD student they knew. He had his alerts set up and was doing everything right by the usual standard. But a paper came out that overlapped directly with his dissertation work. He found out too late. By then, years of work needed to be redesigned. His degree took four extra years to finish.

The paper had been flagged by his alert system. It was sitting there in the folder. He just hadn't seen it.

This is not a story about carelessness. It is a story about a system that was never designed to handle the volume of academic publishing in 2025. Google Scholar alerts were built for a different era. They surface hundreds of loosely relevant results, train you to ignore them, and fail quietly when it matters most.

I decided that before I even started my own PhD, I would not depend on that system. And if I was going to build something better for myself, I might as well build it for everyone.

Novarum Scholar monitors the literature across five major academic databases every day. You tell it what you study. It watches for new publications that match your research profile and delivers them to your inbox with plain-language summaries, on whatever schedule fits your work.

No dashboard to check. No inbox to manage. No algorithm deciding what is popular. Just the papers that are actually relevant to your research, arriving on your terms.

We built this to replace the anxiety of keeping up with a quiet confidence that you won't miss what matters. The PhD student who runs it should be able to trust that if something relevant was published, they will know about it. Not eventually. This week.

Your data is yours. We use it only to find you relevant papers. We do not sell it, share it, or use it to train models. Your research interests are your intellectual property, and we treat them that way.

My name is Alyx Denison. I built this. I use it. And I built it to be something I can trust as I go into my own PhD work, because the stakes of missing a paper are higher than any alert system should be allowed to risk.