Key Takeaways AI pilots often struggle in production because real enterprise environments are complex. Legacy systems, fragmented data, security requirements, and compliance constraints can quickly expose the limits of a successful demo. Forward Deployed Engineers...
Key Takeaways: AI is changing simulation from a late-stage validation step into a continuous part of product development, helping teams explore more designs, automate setup, and support predictive digital twins. AI-driven simulation still depends on high-performance...
Key Takeaways AI needs lifecycle context to deliver real value: Standalone AI tools often struggle because they cannot see how requirements, designs, code, tests, and quality data connect across the product lifecycle. The digital thread provides the missing context:...
Key Takeaways Visibility, not complexity, is often the real problem: Disconnected requirements, hardware, software, testing, and quality data make it difficult for teams to understand product status and downstream impacts. Data silos create delays and compliance risk:...
Vehicles are only becoming more software-defined. As innovations break into the industry, automotive engineers and Tier 1 suppliers must keep up. Explore how they do so in this eBook.What You Will Learn Discover how: Software has become the differentiator in...
A global leader in stored energy solutions needed to unify its engineering workflows across Codebeamer and Azure DevOps. OpsHub Integration Manager (OIM) partnered with SPK and Associates to deliver a bi-directional, rule-driven digital thread, enabling controlled...
Introduction Michael Roberts: Hello, and welcome back to another SPK & Associates vlog. My name is Michael Roberts. I'm the Vice President of Sales and Marketing here at SPK & Associates, and today we have a special guest. I'm joined by SPK's CEO and...
Key Takeaways Slow engineering onboarding delays productivity: Waiting for workstations, CAD software, VPN access, and engineering data can keep new hires and contractors from contributing for days or weeks. Cloud CAD removes hardware and setup bottlenecks:...
Key Takeaways AI failures are often foundation problems, not technology problems: Engineering AI initiatives frequently stall because organizations lack clear business objectives, trusted data, connected systems, and scalable processes. AI needs connected,...
Key Takeaways Late-stage changes get expensive fast: The farther a problem travels through design, testing, and manufacturing, the more time, cost, and rework it creates. Disconnected systems and weak traceability are major causes: When requirements, design, software,...
Key takeaways Faster engineering does not always require more headcount: Disconnected systems, manual handoffs, rework, and poor visibility often create more delays than a lack of engineering capacity. A digital thread can eliminate major sources of wasted time:...
In many organizations, systems operate independently, creating a large visibility problem. A digital thread addresses this by creating a connected flow of product information across the lifecycle. This playbook explains why engineering visibility matters, and how...