For insurance companies, balancing customer expectations with the rigorous requirements necessary to mitigate risks poses a challenge. Especially when you’re using manual underwriting processes. By turning to artificial intelligence (AI) in insurance underwriting, you avoid costly delays, streamline your employees’ processes, improve accuracy, and create an optimal customer experience. In this blog post, you’ll learn how AI facilitates greater efficiency in underwriting.

Privacy is no longer a growing requirement for doing business — it's the new status quo. The stakes for not protecting it have only intensified. Consumers have been demanding greater control and privacy over their data for years, and now vast numbers are taking action to protect it, turning off tracking, using cookieless environments and relying on ad blockers at rapidly increasing rates.

According to Gartner, ‘By 2026, the market for software that enables hyper-automation will reach nearly $1.04 trillion, with a CAGR of 11.9%. Demand for hyper-automation is driven by a strong need for digital transformation due to talent shortages, increasing economic pressures, and competitive challenges.’

With the globe becoming more and more digitally linked, mobile applications are becoming an essential part of our everyday life. We use smartphone applications for a wide range of purposes, from healthcare and education to banking and shopping. It's important to understand, though, that not everyone uses these applications in the same manner.

What if a single software glitch could cost your company millions? In today’s digital world, that’s not just a possibility – it’s reality. As businesses double down on digital-first strategies, software powers everything from critical infrastructure to day-to-day consumer experiences. Even minor bugs can cause massive disruptions, halt business operations, and compromise customer trust. The margin for error has never been smaller.

Data pipeline automation plays a central role in integrating and delivering data across systems. The architecture is excellent at handling repetitive, structured tasks, such as extracting, transforming, and loading data in a steady, predictable environment, because the pipelines are built around fixed rules and predefined processes. So, they will continue to work if you maintain the status quo, i.e., as long as your data follows a consistent structure.

One of the benefits of Ruby's developer-friendly syntax is that it's straightforward to quickly build scripts to automate tasks. Web scraping with Ruby is fun, useful, and straightforward. In this article, we'll explore using HTTParty to pull a web page and check it for a given string. To be specific, we'll build a cron job in Ruby to check if a product is in stock on a website!

Before we dive in, we want to remind our readers that the Konnect engineering team actively uses Kong products like Kong Gateway, Kong Mesh, and Insomnia. In this post, we'll showcase the power of Kong Gateway and two plugins — the JQ and Request Transformer Advanced Plugins — to govern and configure APIs, and explain how it played, and continues to play, a crucial role in the release of a new v2 Konnect API specification. The key takeaway here is: don’t do more work than is necessary.