Whether you’re working in the marketing department or the operations department, you’ve probably heard a lot about APIs and API integrations. API integration is the process of connecting different software systems or applications through their respective APIs to enable them to communicate and share data seamlessly. These have become the “buzz” terms of IT departments in recent years as more enterprises embrace the trend toward digital transformation.

In 24.2, we introduced our enterprise copilot. Enterprise copilot allows you to upload business documents and collect them in knowledge sets. From there, you can ask questions about information in these documents and receive answers quickly. For instance, an organization with a heavy regulatory burden could upload legislative and operational documents. Then, these employees could get insights from Appian AI Copilot to ensure they adhere to compliance requirements.

Ready or not, AI workflow automation is poised to transform business operations from the shop floor to the C-suite in the AI economy. As organizations embrace digital-first initiatives, IT teams will be able to do much more with less. The situation is a byproduct of the generative AI boom. And yet, so many companies have hardly scratched the surface of AI automation’s full potential in their business operations.

Performance testing is a form of software testing that focuses on how a system running the system performs under a particular load. This type of test is not about finding software bugs or defects. Different performance testing types measures according to benchmarks and standards. Performance testing gives developers the diagnostic information they need to eliminate bottlenecks. In this article you will learn about.

Unit tests are essential to verify the behavior of small code units in a Node.js application. This leads to clearer design, fewer bugs, and better adherence to business requirements. That's why Test-Driven Development (TDD) and Behavior-Driven Development (BDD) have become so popular in the backend development community. In this tutorial, we'll dive into unit testing and understand why it's needed in your backend.

It's 2024, and the HyperText Transfer Protocol (HTTP) is 35 years old. The fact that the vast majority of web traffic still relies on this simple, stateless form of communication is a marvel in itself. A first set of content retrieval optimizations were added to the protocol when v1.0 was published in 1996. These include the infamous caching instructions (aka headers) that the client and server use to negotiate whether content needs refreshing.

You’ve built an incredible AI API and are ready to release this functionality to your users. The issue is that you’re not sure exactly how to monetize it. Generally, monetizing APIs is challenging at scale, but monetizing AI APIs can be even more difficult. Some AI APIs may be charged on a “per API call” basis, but many AI APIs require charging users for input and output tokens used within an API call. Others may charge per unique user or API key.