Systems | Development | Analytics | API | Testing

Building a Business Case for Test Automation in Insurance industry

Insurance companies face unique challenges in delivering reliable software quickly. Policy updates, claims processing, and regulatory compliance all demand precision and speed. Manual testing alone can create delays, introduce errors, and increase operational risk. That's where test automation for insurance industry comes in. Repetitive regression tests that previously take up so much time can easily be automated.

Fix an error in Copilot without leaving your IDE

Production errors are every developer's nightmare. You're enjoying your coffee when suddenly alerts start firing - users are experiencing crashes, and you need to find and fix the issue fast. Today, we'll walk you through how to use AI to diagnose and fix critical errors in an application using Rollbar's MCP (Model Context Protocol) server.

Securing Government Procurement with Low-Code Platforms

Procurement applications sit at the heart of government operations. These systems are prime targets for cyber attacks because they manage critical, high-value data, including: They also connect with core enterprise systems (e.g., ERP, HR, financial management), creating additional risk points. In the wrong hands, this data could allow adversaries to piece together strategic mission capabilities. In this environment, security isn’t optional—it’s foundational.

Cloud vs. On-Premise: Incident Response with DreamFactory

When it comes to handling security breaches, cloud and on-premise environments offer vastly different incident response approaches. Here's what you need to know: Cloud setups prioritize speed and automation. They reduce recovery times by up to 80% with tools like automated playbooks, real-time monitoring, and built-in redundancy. On-premise systems offer full control over hardware and data but rely heavily on manual processes, leading to 25% longer recovery times on average.

Load Vs Performance Vs Stress Testing: Differences & Examples

Load testing, performance testing and stress testing are often mixed up, but in today’s CI/CD pipelines and production-grade engineering, they are solving completely different purposed. If you want to: Automate testing within CI/CD pipelines, such as with Keploy, JMeter, Locust, or k6 This guide discusses the difference like Performance testing, Load testing and Stress testing.

Managing Risk in Banking and Capital Markets with Qlik and Databricks

Discover how Qlik and Databricks are transforming risk management for banks and capital markets Learn how leading financial institutions are leveraging data and AI to manage risk, prevent fraud, and stay ahead of industry regulations. Learn how modernizing your data estate and harnessing the power of artificial intelligence can streamline compliance and automate complex processes. Get a sneak peek at the tools and strategies that help banks get AI-ready, integrate data pipelines, and unlock the benefits of generative AI.

Driving Sustainable Innovation: Our Approach to Green IT & Sustainability Testing

In today's digital-first world, we face a profound paradox. The technology that connects us, powers our businesses, and fuels innovation is also leaving a significant and growing impact on the environment. Data centres use more energy than certain nations, harmful code wastes gigawatts of electricity, and the ongoing need for more powerful gear means that creation and disposal never stop.

AI Data Enrichment: Turning Your Business Data into a Strategic Advantage

In the age of automation, raw data isn’t enough. Businesses are now realizing that AI data enrichment, which is the process of enhancing existing data with intelligent, contextual information, is the key to unlocking more accurate insights, better personalization, and more efficient operations. The challenge? Making enrichment operational. That’s where Integrate.io comes in.

Speedscale Proxymock: Freely testing cloud native apps alongside AI code assistants

We’ll always remember 2025 as the year AI code assistants went big. Copilot, Cursor, Claude, Windsurf, whatever. Developers went from mistrusting these tools, to being expected to turn over much of their coding labor to them. Even if, according to an extensive Stack Overflow survey, only 3 percent of professional developers say they ‘highly trust’ AI coding tools.