Systems | Development | Analytics | API | Testing

As businesses race to become data-driven, the ability to quickly build and iterate on data workflows is more critical than ever. Traditional ETL and ELT processes, while powerful, often require extensive coding, long development cycles, and high maintenance overhead. Enter low-code data pipelines: a modern, visual-first paradigm enabling faster development, broader accessibility, and better scalability.

As enterprise data increases in volume, variety, and velocity, the need for a new data architecture is becoming clearer. As AI moves from generative to agentic, can enterprises also envision and adopt an agentic data architecture? It’s true that we’re already seeing AI agents implemented in functions such as customer support and marketing. But what if we could do the same for data management?

In insurance, the claims process is the real “moment of truth.” It's when customers find out if their insurer is truly there for them. They don’t just want fair treatment—they also expect their claims to be handled quickly and easily. But the reality? Claims often take way too long because of outdated, clunky processes. And the growing tsunami of data needed to adjust a claim can create information overload for an adjuster.

In March 2024, the European Union passed the AI Act. This sweeping regulation reshapes how organizations deploy and manage AI systems. The law addresses AI risks that could affect both individuals and businesses, from hiring biases to critical infrastructure failures. Similar rules have started taking shape across the world, including several state-based regulations in the US. But the regulation is only the floor. We all share the responsibility of creating a safe, responsible AI future.

AI is a groundbreaking technology that is ready to modernize the way federal government agencies operate. By automating tasks and optimizing workflows, artificial intelligence (AI) promises to enhance efficiency, minimize errors, and boost productivity without adding resources. But as with any change—and especially one as transformative as AI—leaders need to take deliberate and cautious steps to ensure a smooth integration of these innovations and to gain the buy-in of government employees.

To be good stewards of taxpayer dollars, state and local governments conduct market research and perform due diligence before purchasing a software solution. Commercial off-the-shelf (COTS) products are often positioned as offering the best price tag and the fastest deployment. However, the promise of a speedy installation often goes unmet.