Laboratory equipment is one of the quiet barriers that determines who gets to do research. A well-funded lab replaces instruments on a cycle, while a startup lab may go without entirely because the new price is out of reach. Pre-owned equipment can cost up to 80% less, but the secondary market is so fragmented that many labs never access it.
MerkaLoop is building a marketplace for affordable laboratory equipment, using AI agents to handle transactions that used to take months of phone calls, PDFs and chasing documentation.
Emilia Vandamme is MerkaLoop’s co-founder. She and her co-founder Annabel Vago met at school at 15, both ended up at J.P. Morgan, and left together to start the company. We spoke about circular infrastructure for science and why impact should be structural rather than decorative.
Can you introduce yourself and tell us about your role?
I’m Emilia Vandamme, co-founder of MerkaLoop, the marketplace for affordable laboratory equipment, pre-owned and new. We’re changing how the world’s laboratories buy and sell scientific instruments, with AI agents handling the transaction process that used to take months. I run the company with my co-founder Annabel Vago, and my days span everything from looking after our suppliers and buyers, to shaping the product with our CTO, to deciding which market, deal or hire comes next. What excites me most is seeing equipment take on a second lease of life. Outside of work I freedive, kitesurf and skydive… all sports where your life depends on trusting your equipment, so of course I went and built a company on the same idea.
How did your company come about and what was the motivation behind it?
Annabel and I met at school when we were 15, and we knew even then that we wanted to build a company together. Years later, by pure coincidence, we both ended up at J.P. Morgan, and we left together to start MerkaLoop.
We’d each run into the same problem from opposite ends. At J.P. Morgan I was in Alternative Investments, investing in biotech-focused funds, and I saw first-hand how much biotechs were overpaying for laboratory equipment. Annabel had started her career in audit at Deloitte, where part of the job was literally counting lab equipment, and she noticed the other side of it: how much of that equipment was sitting idle. One side was overpaying, the other was letting good instruments gather dust, and there was no functioning market connecting them.
When we dug in we found a market worth over sixty billion dollars that still runs on phone calls, PDFs and personal networks. A deal for a single instrument can take months, so brokers only bother with the biggest ones, and everyone else is left to pay full retail or go without. What made now the moment to act was AI: for the first time, the end-to-end work that kept this market manual could be automated.
Can you describe your company’s mission and values?
Our mission is to become the global loop for lab equipment, moving every instrument from the lab that’s finished with it to the lab that needs it next… it’s in the name. Every year, billions of pounds of laboratory equipment sits idle or goes to waste while new and growing labs struggle to afford what they need, and we’re building the circular infrastructure that fixes it: a trusted marketplace where labs, universities, hospitals and startups can buy and sell verified equipment. The goal is to accelerate discovery while reducing waste, and to make reuse the default in every lab in the world rather than a nice-to-have.
Three things we stand for alongside impact:
1. Access: every lab anywhere should be able to afford quality equipment.
2. Trust: buyers and sellers verified and every instrument carries verified condition and history, in an industry that has run on opacity for decades.
3. Efficiency: AI agents stripping out the months of manual work that made reuse more hassle than buying new.
What makes us different is that labs come to us because pre-owned saves them serious money and gets them equipment faster, and the environmental benefit happens whether they care about it or not… which is, in the end, how you actually make reuse the default.
What are some of the most pressing social issues that your company is working to address through its technology?
Two issues sit at the heart of what we do.
The first is unequal access to science. The cost of laboratory equipment is one of the quiet barriers that determines who gets to do research. A well-funded, mature lab replaces instruments on a cycle, while a startup lab may go without the equipment entirely because the new price is out of reach. Pre-owned equipment can cost a fraction of the list price, up to 80% cheaper, but the secondary market is so fragmented and untrustworthy that many labs never access it.
The second is waste. Laboratories are resource-intensive by nature, and equipment turnover is part of that. Instruments with years of useful life left are decommissioned, stored indefinitely or scrapped because selling them is too much hassle.
Technology is what makes our approach possible. AI agents can do what a human broker does, matching demand to supply, chasing documentation, coordinating logistics, but they can do it across thousands of instruments and dozens of countries simultaneously. That drops the transaction cost enough that deals which were never worth a broker’s time become viable.
Technology doesn’t solve trust on its own though, we always have a human in the loop!
How does your company measure the impact of its work in creating positive change?
I’ll be honest that we’re early, and I’m wary of companies our stage claiming big impact numbers.
There’s one thing we do on every single deal already: we plant a tree for each piece of equipment sold through MerkaLoop. It’s a small gesture in addition to the emissions avoided by reuse itself.
Buying pre-owned avoids the manufacturing footprint of a new instrument, and we’re working towards putting a credible avoided-emissions figure on transactions. We’re also a channel partner for My Green Lab’s ACT Ecolabel, the environmental impact label for laboratory products, so sustainability data becomes part of how our buyers choose what they purchase.
The measure we care about as well, but is the hardest one: the research that happens because a lab could afford an instrument it otherwise couldn’t. As we grow, collecting those stories from our buyers will matter as much as any dashboard.
In your opinion, what impact will technology have in creating a better future?
I’m optimistic, with caveats.
The shift I have a front-row seat to is AI agents taking over transactional drudgery. So much of the world’s commerce, especially B2B, runs on humans doing repetitive coordination work: chasing quotes, matching buyers to sellers, filling in customs forms, reconciling invoices. That work is expensive, and its expense is why whole categories of useful transactions simply don’t happen. When agents can do it, markets that were too inefficient to exist start working. The same pattern will play out in dozens of industries over the next few years.
For science specifically, the two shifts compound: AI accelerating research itself, and better markets making the physical tools of research cheaper and more available, because a brilliant model still can’t run your samples.
The caveat is that none of this is automatic. AI agents transacting on people’s behalf need to be trustworthy, transparent about who they represent, and accountable when things go wrong. We think about that constantly as we build ours, and it’s why we keep a human in the loop on every deal: real money and real equipment moving across borders is a responsibility to earn deal by deal, and the technology will only create a better future if the people building it treat it that way from the start.
What advice do you have for other companies looking to use technology for good and create a positive impact in the world?
Find impact that’s structural rather than decorative. The best tech-for-good companies don’t run impact as a separate initiative from the business, because the core transaction is the impact.
If you can only articulate your mission in a separate paragraph from your revenue model, that’s a signal the two aren’t connected yet, and the mission will be the first thing cut when times get hard. Impact and margin should reinforce each other.
If growing the business only sometimes produces the positive outcome, question the model, because the strongest examples are ones where you can’t hit revenue targets without the impact happening… they’re mathematically the same thing.
That’s the test we set ourselves with MerkaLoop: every deal we earn commission on is also an instrument a lab could afford and a machine kept in use, in the same moment.
And a final note: if you’re on the fence about starting a tech-for-good company, the gap between watching a problem and working on it is smaller than it looks, especially with AI today. I’d encourage anyone tempted to make the jump.
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MerkaLoop is early, and Emilia is upfront about being wary of companies at their stage claiming big impact numbers. The measure they care about most is also the hardest to capture: the research that happens because a lab could afford an instrument it otherwise couldn’t.
You can find out more at merkaloop.com.
