How do you get into this kind of business? Before you have any customers you would not have any data to train a detection algorithm right? So how can you bootstrap the entire product? Is it solely based on connections to buyers?
Why do you assume it's bootstrapped? We have followed a similar path at Aidlab (although we raised a modest $2M instead of $41M), but we had a clunky prototype and a strong pitch deck with a solid team. Sometimes that's enough!
I didn't mean bootstrapped in terms of funding but in terms of building the product. Like how do you get the data to build the product that makes the product worth buying in the first place?
I don't think you can separate these two things in medtech/hardware. It's almost impossible to build a product without money, and you certainly can't bootstrap this.
> Like how do you get the data to build the product that makes the product worth buying in the first place?
Our path:
1. Raise the money.
2. Build a better prototype (let's call it a 'data collector').
3. Create datasets from the new prototype through studies/clinical trials.
4. Apply ML.
5. Develop the next iteration with the newly built models.
In many countries, health is not a business, but a research topic. As a result, databases, cohorts, studies and other data collections can exist without being monetised, or being monetised within some contractual bounds stricter than what happened with LLM training data. So, to get a head start, you would connections in the medical world, and cardiologists, to get access to this data (that already exists). And you would need those professionals for analysis and feedback of your product too
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[ 3.8 ms ] story [ 23.6 ms ] thread> Like how do you get the data to build the product that makes the product worth buying in the first place?
Our path:
1. Raise the money.
2. Build a better prototype (let's call it a 'data collector').
3. Create datasets from the new prototype through studies/clinical trials.
4. Apply ML.
5. Develop the next iteration with the newly built models.
6. Profit time.
https://newsnetwork.mayoclinic.org/discussion/mayo-clinic-la...
https://anumana.ai/ecg-ai-lef