Releasing a beta version of a Node.js package is a common practice when you want to share a new feature or a breaking change with testers or early adopters without affecting your stable users. Beta releases are tagged with a special version identifier (like 1.0.0-beta.0), making it clear that the version is pre-release and not production-ready. In this guide, we will cover the steps to release a beta version of your package using npm, ensuring a smooth and controlled release process.

Organizations are in a sheer need to stay up-to the minute, and be ahead for protecting their systems and data. Penetration testing can prove to be a structured process that can mimic the real-world vulnerabilities before it’s prone to any malicious exploits. In this entire lifecycle of pentesting, we got some tools in order to automate, streamline, and enhance each phase of it. They could be of various types, based on their specific role in this entire lifecycle.

The need to democratize and share data inside and outside your organization, as a real-time data stream, has never been more in demand. Treating real-time data as a product, and adopting Data Mesh practices, is the way forward. Here, we explain the concept through a real-life example of an airline building applications that process data across different domains.

AI is proving that it’s here to stay. While 2023 brought panic and wonder, and 2024 saw widespread experimentation, 2025 will be the year that financial services enterprises get serious about AI's applications. But it’s complicated: AI proofs of concept are graduating from the sandbox to production, just as some of AI’s biggest cheerleaders are turning a bit dour.

In today’s digital world, user experience (UX) plays a key role in a product’s success. Studies show that 88% of online users are less likely to return to a website after a poor experience.

Documentation forms an integral part of operations in almost every industry. Take logistics and transportation, for example, where companies process hundreds of thousands of documents daily to keep the goods in motion and the supply chain functional. So, what are logistics companies doing to handle such a vast number of documents? More importantly, how can they use the intelligent document processing (IDP) technology to manage their documents and extract the data they need?

Businesses across various sectors want to leverage AI to increase efficiency, reduce cost, enhance customer experience, or do all that in one go. The mortgage industry is feeling it, too, thanks to the several potential areas where AI technologies can impact. For instance, AI can help mortgage lenders by: In fact, according to a Fannie Mae survey, mortgage lenders believe compliance, underwriting, and property valuation are all ripe for AI integration.

Government organizations are under pressure to deliver more efficient, transparent, and responsive services. Digital transformation is accelerating the pace of change. Public sector organizations that rely on manual processes can no longer keep up with the demands of modern governance. This is where workflow automation comes in. Automation is a powerful way to streamline operations, enhance service delivery, and improve decision-making.