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I built an AI that answers questions based on user research data.
A guide to building an AI with a custom knowledge base using OpenAI API.
Modern products often have a large amount of user research data from different sources: user research interviews, intercom conversations, customer e-mails, surveys, customer reviews on various platforms, etc.
Making sense of all that data is a challenging task. A traditional way to do that is to maintain a neatly organized database with various corresponding tags.
But what if we can have our personal AI chatbot that can answer any question about our user research data?
By querying a large amount of historic user research data, the chatbot can provide insights and recommendations for a new project, product, or marketing campaign.
Well, now it’s possible with just a few lines of code. You can do that even without a technical background. In this article, I’m going to explain how to do that step-by-step.
This technique was first described by Dan Shipper.
![](https://miro.medium.com/v2/resize:fit:700/1*1d06KIu99qQsm_J7SGVEGQ.png)
OpenAI API
You are probably familiar with ChatGPT and hopefully are already using it in your working process. If not, I recommend reading my article about AI's impact on design first.