Building a startup can be challenging. But wanting to integrate artificial intelligence (AI) to that endeavor makes it a daunting experience—especially at the beginning, since startups usually lack in-house developers and the capital necessary to tackle such complicated projects. But not to worry, today we’re breaking down how to integrate and build AI as a startup.

Where to start?

How to integrate AI in the early stages of your startup

Building AI from scratch is not something a startup can do from day one. Instead of running before crawling, you should rely on pre-existing solutions. Even though they are not as customizable, they are much less expensive and can still provide a taste of what you are setting out to do—attracting clients or investors and hopefully leaving them wanting more.

Data is key

To be a little more specific, we can use a client of mine from six months ago as an example. Let’s say you’re a startup that ultimately wants to build AI to analyze data. The very first thing you’re going to need is… you guessed it: data—and lots of it. Create the biggest database possible. This will come in handy when using machine learning techniques, finding patterns to ultimately get an algorithm you can profit from.

To create your own database structure service, I suggest using Compose.io which provides Database-as-a-Service (DBaaS). In order to collect data, there are ETL (Extract, transform, and load) tools. Talend is a great ETL where you can synchronize various formats or connectors, such as API, FTP,  JSON files,  CSV files or external databases, etc. You are probably going to need a data scientist further down the road, but for now, you can get more info about these tools on the Web, and play around with them.

Next, you need to understand and give a voice to all of this data, and a great way to do just that is through visualizations. Keep in mind that business intelligence is all about making data speak. A great tool for this is Tableau, where you can create a dashboard and improve it with customer use cases, and present your data more efficiently. This will be the beginning of your AI journey. And done right, it will definitely be enough to jump start your investments.

The truth about artificial intelligence

Advantages and disadvantages of using AI

Artificial intelligence has proved to be very useful for prediction, image recognition and understanding human language—a.k.a NLP or Natural Language Processing, for which we already have existing algorithms available that have been trained for millions of hours.

However, AI is still somewhat unpredictable. You never know the quality of the deliverables you might get. Think of Siri, Cortana or Google Assistant—they can be incredibly helpful but still get things wrong sometimes. Even though these misunderstandings may make for a funny meme, it’s less funny when it tampers with your business.

Artificial intelligence development

Since we cannot know ahead of time what the result will be, you can’t trust the machine 100%. There is a certain type of intelligence that only humans can achieve, so enrich the process through human-guided machine learning. The truth is, developing AI requires lots of time and money, so make sure you invest in good people to fill in the gap between natural and artificial. Get someone specialized in machine learning, deep learning or neural networks, to understand different behaviors. For machine learning, for example, you will usually need someone who knows Python—and you need to specify everything—from the data that you have, to the results you want to get.

A great adventure

You can definitely build a startup with AI

Building AI as a startup is feasible, but you need the right people, tools and business model beforehand. Get yourself together and show that you have control over your market, that you know what’s needed and have the data to support it.

You can even go ahead and check out my Startup Roadmap Definition course to better identify when to integrate AI into your project, how to plan out your development, and show investors, accelerators, and incubators what you can bring to the table.

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