‘Software is eating the world.’ - Marc Andreesen
Spotify knows what type of music I like. Google Chrome knows what I spend my time on. My iPhone knows my sleeping pattern. Twitter knows what I’m thinking (many of us have alt accounts, lets not pretend).
The point is we have more data on ourselves than ever, surely we can do more with it than just really targeted ads (no shade to ads by the way, it helps make a lot of things accessible, which we appreciate.)
Turns out we aren’t the only ones who think this. There is a whole field dedicated to this called quantified self.
So, we decided to put this theory to the test - could we aggregate all of our data and paint an objective picture of ourselves? What could we discover about ourselves that we otherwise couldn’t have guessed? And thus, fusion was born.
We aggregate all of your data (with your consent), and provide you with actionable insights on your behaviour to help you better live the life you want to live - both professionally and personally.
As a user we don’t require you to do anything, apart from getting your consent to extract data from your apps.
For now we aren’t monetising this. We are more interested in seeing if we can produce something of value. If it turns out that we were right then we will consider the following models: freemium, saas or tokens. We won't sell your data or do targeted ads, ever.
No. We can’t see your data. This data never leaves your device as fusion is run locally.
So...let’s see fusion work.
We tested fusion on Ore (one of our co-founders) and the results were… interesting.
For Ore, the biggest question he had about himself was “what helps me do more neurotech work?”
These were his top 3 results:
With further investigation we were able to figure out some of the driving behaviours behind these correlations.
For example, we found out that the best time for Ore to do exercise (if he wants to do more neurotech work) is to do so in the early hours of the morning between 5-7AM.
This is just the tip of the ice-berg. We as humans are complex systems, whose outputs depend on a number of different variables, so it is unsurprising that we only get weak correlations when we compare two variables.
Why is it important?
What would happen if you were 1% more productive? Or if everyone was x% more productive, happier etc? To be honest, neither of us are sure, but we believe it’s a question worth exploring.
We see fusion being used with healthcare data, enterprise data and much much more. We hope that fusion can be the tool that helps people better understand themselves, and eventually the world.
For now, our next steps are the following:
This, however, is subject to change depending on the input of our community members.
We have accomplished quite a bit as a small team of two, but we still need some help - that’s where you come in.
We are looking for the following people:
It’s time to build.
\\ Adaobi & Ore