While public APIs for NLP models provide a fast time-to-market, you just might be giving up your competitive advantage by not building in-house.

We constantly adjust the way we communicate based on the context. In our house versus the office. To a friend versus a potential customer. We’re always framing our language and tone based on where we are and who’s listening.

Natural language processing (NLP) is no different. Only when your domains and models match the work your organization is trying to get done—or the problems you’re solving for your customers—can your NLP journey truly take off.

Your organization’s text data is a goldmine of transformational knowledge, but traditional structured methods of analyzing text, like regex and boolean chains, aren’t going to cut it long-term.