Structuring energy billing data with OpenAI for later BI

Did you know that ChatGPT can be used programmatically to extract information from invoices and structure it in a database, allowing you to perform Business Intelligence on the data afterward?

Today, I had a consulting session with an energy company that has to extract their customer bills into a table to analyze the data later.

Instead of creating a parser for each provider, create an algorithm in LangChain to structure the output and later put it on a table.

Before developing an algorithm, consider all options available because you’ll save a lot of time.

In this case, let’s say it costs you 10 hours to develop the algorithm to extract the billing information of a single provider. If your bills can be from 5 different providers, that’s 50 hours of developing algorithms.

Then, imagine the providers changing the billing format from time to time.

Quite a nightmare, innit?

With LangChain, you create 1 algorithm that can be applied to any bill.

That’s what scaling processes mean.