Before low-code, enterprise IT teams had to use either traditional development or commercial off-the-shelf software to provide business solutions. But when low-code development entered the scene, teams discovered they could create custom, enterprise-grade software applications up to 10x faster.

Prior to 2022, a lot of the AI news centered on use cases like self-driving cars. Of course, use cases like these didn’t exactly apply to enterprise software. In 2023 ChatGPT showed the abilities of AI to mimic human language, but still, this only scratched the surface of AI applications for the modern enterprise. If you’ve ever asked yourself, “What is AI capable of?” then consider the following examples: How many emails do you get per day?

The class of 2027 saw a massive influx of applications at top universities across the United States. Harvard received close to 57,000 applications for the class of 2027, while MIT received almost 27,000. UC Berkeley and UCLA, meanwhile, received 125,874 and 145,882 respectively. Manual transcript processing is an uphill battle for educational institutions at every level.

Did you know that the average enterprise utilizes over 1,500 APIs to drive its digital operations? APIs play a pivotal role in today’s data-driven landscape. However, few know the impact API architecture has in enhancing API performance.

With all the recent discussion about the use of artificial intelligence (AI) and large language models (LLMS) like ChatGPT, you may think that AI is a new phenomenon. But in fact, the US Department of Defense (DoD) has been investing in AI for more than 60 years.

With more emerging players entering the insurance market and insurance companies recognizing the importance of the digital experience, consumer demands for a connected insurance experience have grown to new heights. For insurance customers, the claims process is a critical moment of truth, making it essential that insurers deliver a hassle-free, seamless experience with faster claims processing and excellent customer service.

Inefficient operational processes often lead to bottlenecks, delays, and increased costs, hindering a company's ability to respond swiftly to changing market demands and optimize its supply chain management. Enter Business Process Modeling and Notation (BPMN), a powerful visual language that helps businesses enhance operational efficiency and streamline complex processes.

Artificial intelligence has been instrumental in helping businesses streamline and speed up business operations by automating repetitive tasks. It also frees up workers to focus on higher-level tasks that require human intervention. And when paired with other intelligent automation tools, such as robotic process automation, it can improve business processes and provide a competitive advantage.

Generating files for data extracts, reporting and even data migration is a crucial part of any back-end team. A typical data team will have to generate many files to be sent to various clients or consumers inside or outside of the organisation. As with all things, the question is how can the generation of those files be made simpler, and can it be automated to such a degree that files are dynamically generated? The short answer is yes, it can be done dynamically.

Project management across multiple teams, especially under the triple-constraints of time, cost, and scope, is an intensive task. Project managers have to cover tons of ground to keep things on track. For example, they might manage allocating resources based on availability, assigning tasks, controlling execution, tracking and reporting progress, and forecasting future trends.