Systems | Development | Analytics | API | Testing

Understanding ISO/PAS 8800 for AI in Automotive Safety

With the rise of AI use in vehicle software development, concerns arise around its presence in safety-critical applications, especially when it comes to functional safety and regulatory compliance. ISO 26262, the essential standard for automotive development that requires processes for managing, designing, and verifying safety-critical systems, still applies. However, it can fall short when applied to AI models, which are inherently non-deterministic and continuously evolving.

Hevo's Next Evolution

Every company has an AI roadmap. Very few have the data infrastructure to execute it. At Hevo Data, we've spent 8 years building pipelines that are reliable, simple, and transparent so 2,000+ data teams can build without second-guessing their data. We sat down with Manish Jethani, Amit Gupta, and Scott Husband to talk about what comes next. If your data isn't AI-ready, your roadmap stays a roadmap. We've re-engineered the platform to serve as the context engine your AI vision actually runs on. Because the models are only as good as the data underneath them.

Why 90% of AI Projects Never Leave the Pilot Phase? #ai #shorts #softwarearchitect

Struggling to scale your AI? You aren’t alone. Shafrine from WSO2 identifies the bottleneck holding companies back: Data Silos. Without integration, your AI agents lack the "context" needed to be useful in a production environment. Learn how to bridge the gap between a "cool pilot" and a "scalable enterprise agent" by fixing your fragmented workflows.

How Manufacturing Leaders Deploy AI Faster with Governance-First Architecture

AI workflows for manufacturing need to be deployed quickly. Quality control systems, predictive maintenance tools, and supply chain optimization algorithms may be going live, yet compliance infrastructure is lagging behind. The result is a familiar pattern: pilots that prove out technically but stall before production because they can’t clear audit, safety, or regulatory review.

Why Audit Logs Matter for AI Governance | DreamFactory

Audit logs are essential for making AI systems accountable, reliable, and compliant with regulations. They act as a record-keeping system, documenting every critical interaction within an AI system, such as user prompts, model decisions, and policy enforcement. Here's why they are crucial: Audit logs are not just a legal requirement - they are a key part of managing AI systems effectively and minimizing risks.

AI Infused Development of Intelligent & Smart Traffic Management System

The traffic visuals you see in movies shot in the USA, UAE, or even the UK, for that matter, you know how managed and clean that looks. But do you still think that it’s all fiction? Well, if you are, then you’ve got it totally wrong. The way the UAE, the USA, and even Japan manage their traffic is just phenomenal, and it’s all thanks to a smart traffic management system you didn’t know about.

AI Testing Best Practices - Why Human Governance Separates Real AI Platforms from Hype

There is a scenario playing out in QA teams everywhere right now. A team adopts an AI testing tool, runs it for the first time, and gets 300 test cases in minutes. The demo worked. The ROI math looked great. But three sprints later, 60 of those test cases are validating requirements that were updated in the last sprint. Twenty more test a user flow that was deprecated. The AI performed exactly as advertised. The governance system never existed.

Enterprise AI Infrastructure Security Series - 6) Application Gateway

In this video, we pivot from securing your development environment to protecting your production model serving with ClearML's AI Application Gateway. We walk through how to establish a secure front door for your models, manage access with token-based authentication, and enforce governance with stable routes and RBAC to secure your deployed API endpoints.