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Naologic Transforms ERP Operations with MongoDB to Enhance AI Application Development

Photo of a man and woman looking at a computer screen.

INDUSTRY

Computer Software & Technology

PRODUCT

MongoDB Atlas
MongoDB Atlas Vector Search

USE CASE

Gen AI

CUSTOMER SINCE

2020
Naologic is a platform that empowers companies to build AI applications on modern tech stacks, enhancing employee resource planning (ERP) operations. By leveraging MongoDB Atlas and Vector Search, Naologic enables rapid development and integration of AI-driven solutions, allowing businesses to scale efficiently and adapt to their unique needs.
Gabriel Paunescu, CEO, discusses how Naologic leverages MongoDB for AI-driven operational efficiency. This transcript has been edited for clarity.

Naologic is a platform that helps companies leverage AI by building applications on top of all of the modern AI stacks today. Our product augments the operational side of ERP. We started three years ago working with enterprise companies to help them build internal applications much, much faster than using traditional development.

We created a visual way to create very complex data models that allowed our customers to scale their existing legacy platforms. The big picture is that every company on Earth should have custom software running their business without having to pay tens of thousands of dollars or without having to accept general purpose solutions, which are good enough for some use cases but not for all the use cases.

We started playing around with other NoSQL platforms and what stuck out about MongoDB was the developer experience. It was also pretty easy to deploy and gave us the flexibility in the data model without having to constantly shift your tables. So our main focus is in business intelligence on top of MongoDB to allow our customers to do more and parse out more data, but also to find ways to connect external data sources without us having to remodel the data every single time.

We've done a lot with MongoDB Atlas Vector Search because for business data, there's a huge advantage to being able to run query and vector search in the same place. That's where MongoDB was kind of like a cheat code—you don't have to deploy a second thing in your infrastructure, you don't have to find a way to connect.

One of the benefits that we keep seeing is the fact that aggregation pipelines can be used for pretty much anything. We even have the AI generating aggregation pipelines now in MongoDB based on the user's query and based on the reports that we're running in the background. So what they're seeing is a lot of rapid innovation and a lot more testing with AI because they can build AI pipelines quickly with this new upgrade where it's the AI figuring out your data models and just recreating them in MongoDB. That's hundreds of hours saved.

In my mind in the next five years, having a piece of software that you or somebody else cannot edit is going to be like buying a horse today instead of a car. We want to make it so that it's unimaginable to have software where you have to adapt around it, instead of the other way around.

For Naologic, MongoDB is going to play a pivotal role in our evolution because it sits at the core of our platform.

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