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.

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.

In today’s fast-paced, data-driven business landscape, having a comprehensive view of your operations is essential for success. Dashboards provide a centralized, real-time visual representation of key metrics, tasks, and performance indicators, enabling teams to stay organized and make informed decisions. ClickUp’s customizable dashboards elevate this by allowing users to build and personalize their own layouts tailored to specific needs.

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!

Data transformation is a critical step in the data pipeline process, enabling organizations to prepare and process their data for creating dashboards, reporting, and analytics. The right tools can make this process efficient, secure, and scalable. In this blog, we will explore how data transformation tools handle the most common tasks, such as filtering, aggregating, joining, and cleansing data to move to a data lake or a cloud platform of your choice, and what to consider when evaluating these tools.