Chemical registry application built with low code and AI

In 2022, we were contacted by Astrid Software, a company that, together with Avonova Solutions, wanted to develop a completely new module for the HR system that Avonova delivers to ten of its customers. The module was supposed to be a so-called substance ledger, a digital register to keep track of all the chemical substances found in an industrial workplace.

In order to develop the fabric portfolio as efficiently as possible, the parties wanted to utilize the low-code platform Bubble rather than hard-coding the entire application from scratch. Since Braver had already built NAF Bicycle and other applications on Bubble, we were selected as the product development partner to realize the fabric portfolio.

The product was developed in 2022-2023, and launched in late 2023. The fabric portfolio quickly gained hundreds of paying customers, and today lives as a well-integrated module in a comprehensive HR system that Avonova Solutions offers in the market.

Braver is still involved as a development partner, and looks forward to improving and further developing the application in the time to come. We thank Astrid Software for the trust and look forward to the continuation!

Process and Results

We put a designer, a project manager and two developers in turn, and the fabric portfolio quickly began to take shape. In this project, we have pushed the low-code platform Bubble far and proved that it handles technical complexity very well.

An example of this is that the application was integrated with Avonova's existing digital platform and ID solution, allowing the end user to seamlessly jump in and out of the fabric portfolio without noticing that they have moved from one application to another.

The image below shows one of the main screens in the drug directory, where the user sees an overview of all the chemical substances they have added to the “Your Products” list.

An ideal application for artificial intelligence

Another example is that we have integrated an AI solution into the fabric ledger, which is used to extract data from data sheets in PDF format, which is then automatically added to the fabric ledger. This saves users a huge number of hours of manual data entry, which the AI solution rather does in a matter of seconds!

The screenshot below shows what a PDF data sheet typically looks like (right) and that information such as hazard symbols, hazard statements, and alert level are automatically read out of the PDF using AI (left). A superb application for artificial intelligence.