As you know, cost of acquisition is a major concern for solar companies across the spectrum. Whether you are the size of Sunrun or a smaller mom and pop, it costs a lot of money to acquire customers. We thought it'd be great to see if it's possible to qualify a homeowner without talking to a person.

What it does

It uses's natural language processing to classify and then qualify or disqualify the most critical solar qualification criteria

How we built it

We created a dynamic conversation flow that maps a user through a standard lead qualification flow, while gathering lead information along the way via a customer lead engine. To make the conversation natural and conversational, we used a Natural Language Processing AI library, which we wrote a customer wrapper around.

Challenges we ran into

  1. Just getting the AI to talk at all was very difficult
  2. Styling the application with the non-standard small chat window was tricky

Accomplishments that we're proud of

  1. Classifying and getting the conversational flow to work (and seem natural) without any technical experience.
  2. Run from concept to proof of concept in 10 hrs.

What we learned

Natural language processing is going to change the world

What's next for QUAL-E

Happy hour

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