Palantine Analytics was my first AI startup. I was a bright-eyed, go-getter who hoped to create a storm in the sector. My experience in the startup journey had made me a veteran. It was a learning experience that allowed me to grow as an entrepreneur and learn from my mistakes. GenesisAI is steadily growing in popularity.
According to the saying, wisdom comes from learning from others’ mistakes. Here are some key lessons I have learned about creating a successful AI startup.
A valuable asset for any AI startup is high-quality, proprietary data. It will be crucial in determining whether your startup succeeds.
Before you start, make sure to ask questions about data types, data sources and data strategy.
There are many ways to acquire proprietary data. You can either collect the data yourself or use an ML-based algorithm to manually capture data.
The second option is my favorite, as it provides you with relevant and accurate intrinsic data. Although you might face some difficulties when training your machine initially, once you get the details right, you will be able to harness valuable data that will give you an edge.
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You need to be realistic about the problems it can solve when building an AI-driven solution. You could present a solution that helps sales and marketing or an application-modernization solution.
It doesn’t matter what it is, you need to make it real in order to attract many people. This solution should be the driving light for your AI startup.
Startups are flexible and can easily be incorporated into other offerings or products. However, this will only lead to losing sight of the primary goal. Diversification is not a good idea. Instead, focus on consolidating your position with an existing solution.
Palantine Analytics was a place where we emphasized the importance of staff and employees as growth enablers. When I was hired for GenesisAI, that’s what I tried to do.
We wanted to hire the best talent for the job with consideration of their qualifications and how they would fit into our culture.
Our focus wasn’t just on technical hiring. We wanted GenesisAI to be as diverse as possible. If you look at the business advisory board, you’ll see leaders from all walks of life, from CEOs to professors, who provide a balanced view on how to proceed.
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It is easy to get lost in the details of a startup and lose your subject-matter knowledge. This is when you begin to use jargon and fancy terminologies in order to describe the high-end solution that your Artificial Intelligence startup offers. And this is where the problem begins.
Even if your solution is the best, clients and investors will not be able to understand it. Your AI startup’s solution should be presented in the simplest possible words. To maximize impact, you need to make it as simple and straightforward as possible.
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