How might we scale customised product support for our customers?

It's been a truly massive 2025; if I’ve learned anything from piloting our chemically defined FBS replacement in 15+ Australian laboratories, it’s that even the most basic of cell culture activities varies between labs. Temperature, passaging reagents, thawing processes, cell culture plates; every single one of these variables impacts how cells transition to serum-free media.

Unfortunately, these are exactly the kind of insights that don’t make the most exciting scientific papers. Useful insights are hidden in failed experiments that never get shared.

Media City Scientific is now preparing for launch of our first product. We’ve thought a lot about how important it is to ensure the transition from FBS to our serum replacement product is super, super smooth. That’s why I’m committing to things that don’t scale; to support early adopters, I’ll offer 1:1 time with every single customer. But as we scale - even globally - we want to see that kind of tailored support scale too.

That’s why we’re exploring a collaboration with Carmen Kivisild, PhD and her team at Elnora AI. Their platform is designed to capture negative data and turn it into shared knowledge, so labs can avoid repeating the same dead ends. Together, we’re asking: could the combination of deep scientific expertise and a trained GPT agent effectively support labs to transition away from serum use?

We’re hoping to identify a pilot lab anywhere in the world to test this with us - you’ll get all of Media City’s scientific insights, wrapped up alongside a GPT to test whether this is an efficient way of making the transition.

If your lab is considering a move away from FBS, or if you have stories about a transition-gone-poorly, let us know! Taking notes over here to make sure adoption can be super smooth ✏️