Empowering Automation in Disease Research

Matt B., a Senior Automation Engineer in the computational modeling department at a leading disease research institute, faced a significant challenge. His team needed a solution to enable automated computers within the research institute’s hospital system to communicate with each other. After consulting several software vendors, Matt's team was quoted $125,000 for a solution—a price far beyond their budget.

Despite not being a software engineer, Matt decided to take matters into his own hands. He attempted to build an internal solution using low-code/no-code tools like Microsoft Power Apps but struggled to complete the project. He also experimented with AI tools like ChatGPT but was unable to build a fully functional application.

After further research, Matt discovered Pythagora. He quickly realized that Pythagora was significantly more advanced than any other tool he had tried. Its AI agents could learn from one another and produce functional code. Using Pythagora, Matt built a fully functional application in just one day. Over the next 2-3 weeks, he added additional features to the app, which he now uses daily in his work.

With Pythagora, Matt not only found a viable solution but also transformed his initial struggles into a successful project that significantly benefited his team. The app he built saved his team a substantial amount of money and streamlined their workflow.

The app enables seamless communication between automated computers, allowing them to send XML work lists to each other and process output files that specify where automated robotics have moved samples between microplates. This innovation has made their jobs much easier and more efficient.