Systems | Development | Analytics | API | Testing

Build Modern AI-Ready Infrastructure Without Starting Over

Modernization has reached a tipping point. For organizations running mission-critical workloads—including increasingly demanding AI-driven applications—the traditional approach often adds risk instead of reducing it. But does modernization have to mean costly investments, downtime, and uncertainty? Not anymore.

10 Smart Ways PIs Use Open Source Intelligence to Track Individuals

Are you one of those people who believe that their internet presence fades when they press the delete button? That's cute. In the modern digital era, all posts, likes and comments leave a trail of evidence and a private detective knows how to trace it. With the assistance of Open Source Intelligence (OSINT), professional PIs sift through publicly available data, social media, and Internet habits to reveal the truths most individuals believe to be concealed. Starting with the tracking of unknown profiles to the connection of dots, OSINT has become the arsenal of a modern detective.

Resume builders in the age of AI: How to future-proof your testing career

Just a few years ago, AI’s effect on software development was debatable — would it be as transformative as everyone predicted? But its impact is undeniable. In a 2024 survey, a majority of developers reported using AI in development, a sharp increase from the year before. In a short period of time, developers adapted, integrating agentic AI into their daily operations to boost productivity. Quality assurance teams are not far behind.

Enterprise AI that's Ready for Serious Work: Introducing Appian Composer and Agent Studio

AI agents have exploded. And we use this term intentionally. Tech vendors rushed to put out agent products that don’t stand up to enterprise use with results that were mostly underwhelming and sometimes even catastrophic. Appian took a different approach. While companies are now scrambling to validate the efficacy of their AI, Appian’s AI is field-tested, so the products you get are ready to use and safe to deploy from day one.

How to Choose AI-Powered ETL for Non-Technical Teams

Data teams spend 45% of their time on data preparation, which stifles business growth and delays critical insights. With the ETL market projected to grow from $533 million to $1.28 billion by 2034, businesses face an overwhelming array of choices. Yet traditional ETL tools require specialized coding expertise that non-technical teams simply don't have, creating dangerous dependencies on overburdened IT departments.

AI-Powered Integration: Turning Complex Workflows into Simple Commands

Data integration has long been one of the most time-intensive parts of enterprise IT. Connecting multiple systems, reconciling formats, and ensuring data reaches its destination reliably often requires weeks of preparation before the first record moves. But with AI-powered integration, that timeline compresses dramatically. What once took weeks can now be designed, validated, and delivered in minutes.