Ignition Builds AI Software on MongoDB to Automate Go-To-Market Process

We are building the world's first AI product manager. We help automate the entire product development lifecycle. We always felt like there's a big gap between product and marketing teams and product and sales teams, and that's kind of how Ignition was born.

You can literally take a process that takes almost 90 days, like a product launch process, and then get it done in as little as 90 seconds basically within one click of a button. You could build something like Ignition without MongoDB at its core, but it would probably take way more time—you would invest a lot more in resources and figuring out your infrastructure.

We always use MongoDB Atlas for all our operational data—it's our primary database. We started the company, that was the first database we used, and it's mainly because it's developer friendly and we can store all the unstructured data using the document model—you know, JSON format super easy to use.

But now, again with AI, we just talked about retrieval-augmented generation. And for that, we initially started using a separate vector database. But now we moved over to use Atlas Vector Search because the most important thing is it's easy to have all of your data in one place. It's easy to sync data between your database and your vector index. Now that we are using Atlas Vector Search, we have both the vector search and the operational data in the same database.

So MongoDB has been critical for us getting our Ignition platform quickly up and running and getting it in the hands of the customers, so we're really happy customers of MongoDB. MongoDB was the perfect choice for Ignition.