Sramana Mitra: So, what you’re saying is that you got this input about what the market was looking for, and because they were paying customers on the first piece of the functionality, you were able to get them to give you access to data. Because in all of this, as you know, in building AI products, access to data is one of the big gating items so that you can develop anything without problems.
John Wallace: Yes. We cannot build these products in a laboratory. We need to do it in the trenches with customer data.
>>>
Entrepreneurs are invited to the 633rd FREE online 1Mby1M Mentoring Roundtable on Thursday, February 15, 2024, at 8 a.m. PST/11 a.m. EST/5 p.m. CET/9:30 p.m. India IST.
If you are a serious entrepreneur, register to “pitch” and sell your business idea. You’ll receive straightforward feedback, advice on next steps, and answers to any of your questions. Others can register to “attend” to watch, learn, and interact through the online chat.
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In case you missed it, you can listen to the recording of this roundtable here:


During this week’s roundtable, we dealt with two scenarios that each need to figure out bootstrapping strategies to mitigate the lack of early stage funding.
gestr
First, we had Anthony Dobaj from Draper, Utah, pitch gestr. This discussion is a good case study for crowdfunding as a way of early bootstrapping.
Budysdilpoa
Next, Chetan Barot from Nairobi, Kenya, pitched Budysdilpoa, a super app for Kenya.
You can listen to the recording of this roundtable here:

In case you missed it, you can listen to the recording here:

Sramana Mitra: Now, let’s double click down on the concept of experiments. Once you were in these POC situations and started to gain some traction, what kinds of experiments are customers running?
>>>Sramana Mitra: So let’s double click down on a couple of things here. You mentioned a different dataset. So, what dataset is LiftLab using?
John Wallace: In our last company, we were essentially working with user level data, device level data, and log data. Now, we’re working with aggregated data. So we’re working with time series, and the methods are much more around econometrics. So it, it was a new data set and new algorithms.
Sramana Mitra: And what, what is the source of this data?

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