Systems | Development | Analytics | API | Testing

On September 23 and 24, we hosted AI Engineer Paris 2025 at Station F — a one-day gathering of builders, researchers, and practitioners exploring the future of applied AI. With five talk tracks, 48 sessions, and 25 sponsors, the event brought together the best of the AI engineering community in Europe and worldwide. If you want a full recap of the key themes and takeaways from the talks, check out our event recap blog post.

In today’s data-driven world, companies depend on accurate and trustworthy data to make better decisions. ETL (Extract, Transform, Load) testing is a key factor in data reliability, as it ensures that data is accurately extracted from multiple locations, transformed correctly, and loaded into the target system correctly without loss or error.

‍ In 2025, enterprises are under more pressure than ever to do more with less, be agile, maintain reliability, and support growing adoption of AI, cloud, and hybrid systems. IT infrastructure automation is no longer a “nice-to-have” but is becoming mission-critical. Recent industry research shows just how fast this shift is happening.

Looking to integrate industrial data with modern web applications? Here's the gist: Kepware collects OPC UA data from industrial devices, while Ignition processes and shares it as REST APIs. Together, they bridge industrial systems with web tools like dashboards, mobile apps, and cloud analytics. Key Takeaways: 1. Kepware acts as an OPC UA server, gathering and converting data from industrial devices. 2.

Two data challenges exist across almost all organizations: access and trust. These issues scale exponentially as an organization grows to the point that it can no longer hand around sheets of paper or approve database access. The demand for better data access drove the history of data warehousing, following the ethos that better decisions come from more data and that compute would catch up with demand. However, the hunger for collecting more data didn’t come without a cost.

As enterprises embed gen AI into their workflows, many are discovering a minefield of risks. Data privacy breaches, misinformation, adversarial attacks and hidden bias are just a few of the challenges that can derail gen AI initiatives. These aren't just technical concerns, they're business-critical issues that can erode trust, trigger legal consequences, and tarnish reputations.

ClearML Enterprise v3.27 delivers on the three capabilities most requested by practitioners : clear visibility into compute consumption inside projects, simpler and safer access control for remote sessions and deployed endpoints, and quality-of-life upgrades across the UI. The result is better cost control, stronger governance, and faster day-to-day execution.

We are pleased to introduce Tricentis Agentic Test Automation for Salesforce, an AI-driven solution that makes it possible to achieve high-quality Salesforce environments faster and with less effort. We recently announced Agentic Test Automation, enabling Tricentis Tosca to generate comprehensive, end-to-end tests using natural language. With this update, we are extending this capability and applying the power of agentic AI to your Salesforce environments.

In what has already been an innovation rich year, Tricentis NeoLoad continues to evolve to meet modern performance engineering needs. The 2025.3 release brings user‑centric insights with Core Web Vitals in RealBrowser which can leverage greater scalability through the recent availability of our high‑capacity cloud load generator. We are also continuing to build on our recently updated NeoLoad Web frontend with the addition of new and enhanced features.

Every time a website crashes under load, or a feature responds so slowly that users abandon it, you’ve run into a missing or poorly defined non-functional requirement. Studies show that unclear requirements contribute to nearly 47% of project failures. Most of those failures come from missing or weak non-functional requirements.