Companies that stand still in today’s ever-evolving, fast-paced business landscape are at significant risk of losing competitive advantage. Increasingly, high-quality software is playing a vital role in ensuring that organizations are able to innovate, pivot, and adapt to suit the growing demands of their customer base. However, application testing challenges have significantly hindered the pace at which software can be delivered for too long.

Selenium IDE is a popular open-source tool for recording and running automated browser tests. You can use it to interact with a browser the way a human would, doing things like navigating to URLs, filling in forms, and clicking on links and buttons. You can also use “assertions” to verify things are working as expected, like checking that elements are present, text is present, inputs contain certain values, et cetera.

Snowflake customers can take advantage of Fivetran’s data movement and data replication capabilities as a native application available in the Snowflake Marketplace.

For the last couple of years, Retrieval-Augmented Generation (RAG) architectures have become a rising trend for AI-based applications. Generally speaking, RAG offers a solution to some of the limitations in traditional generative AI models, such as accuracy and hallucinations, allowing companies to create more contextually relevant AI applications.

Epicor’s ability to provide industry-focused, scalable, and customizable ERP solutions has made it a popular choice for organizations across the globe. Epicor’s built-in reporting capabilities are useful for standard reports but can be limiting for organizations that require more advanced analytics. Without deep technical knowledge of Epicor’s data structures, attempting to manually create custom reports can create serious roadblocks to data trust within your organization.

GoReplay and Speedscale are two popular tools commonly used for load testing. Both share traffic shadowing as a core feature. This article compares both tools against the following criteria: For more Kubernetes load testing comparisons, check out our other posts.

Retrieval-augmented generation (RAG) is gaining traction, and for good reason. As businesses and AI experts search for more intelligent ways to process information, RAG combines the best of both worlds, i.e., the vast knowledge of retrieval systems and the creative power of generation models. But what exactly is RAG, and why is everyone talking about it?

In today’s fast-paced world, operational efficiency is paramount for businesses striving to stay competitive. The ability to manage time and resources effectively directly impacts overall performance. Our recent tech paper on – ‘Maximizing Efficiency by Real-Time Detection of Beacon Check-In Delays’, highlights how real-time detection technologies can revolutionize industries by identifying and mitigating inefficiencies caused by delays in beacon check-ins.

If you’re at all familiar with APIs, you know that REST APIs are the main API used, particularly when it comes to microservices and their applications. gRPC is a high-performance, binary, and strongly-typed protocol using HTTP/2, while REST is a simpler, text-based, and stateless protocol using HTTP with JSON/XML.

What do you think of when you think of generative AI? Generating photos, animations, and videos? Coding and solving math problems? Writing content and brainstorming with a chatbot? These have all driven plenty of excitement around AI, but there’s so much more to it than that! From an enterprise perspective, Generative AI’s impact on intelligent document processing technology is remarkable.