We’ve heard it all before: “We need to buy some AI.”
Companies realize that powering their products and operations with artificial intelligence (AI) can help them make sense of their data and give them a competitive advantage.
In 2019, the question is not why deploy AI but how.
As with most technological implementations, the build-or-buy question looms large. There is no one-size-fits-all solution to this quandary and the right answer will depend on a confluence of factors, including how much data you have, your timeline, and your budget.
On the buy side, Austin-based AI startup, SparkCognition, closed a $100 million Series C funding round this week. The company plans to use this capital to expand operations, allowing customers to weave AI into the fabric of their organizations.
SparkCognition has found a sweet spot bringing AI to enterprises through its core product offerings:
Build, buy, or both?
Large funding rounds over the past month have shown us that whether you are looking to build your own AI solution, buy an off-the-shelf solution, or mix and match, there are robust solutions for you on the market.
SparkCognition straddles the line, allowing you to buy some solutions (e.g., SparkPredict, DeepArmor, and DeepNLP), while also providing your data and AI experts a tool to build and maintain machine learning models (Darwin).
Last month’s $206 million funding round from DataRobot for the company's automated machine learning platform is another testament to this phenomenon.
However, not every company has the data science experience necessary to train models and build their own AI solutions. Therefore, another prevalent and prominent approach we have seen is AI consultancy, or artificial intelligence consulting providers. A big player in this space is Element AI, which raised $151 million last month to bring AI to more enterprises.
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