The SAFe Assistant at AgileTech – How AI Gave RTEs Their Role Back

Scaling agility across an enterprise is never a given – especially when distributed teams rely on different technologies within fragmented tool landscapes. As a leading company that develops mechanical components for the automotive industry as well as software solutions, AgileTech knows the pressures of such complexity. To address this, the company had long embraced the Scaled Agile Framework (SAFe) to structure scaling: with clear roles, synchronized sprints, and defined metrics. 

But as structures grew, so did the challenges: more teams, more tools, more processes – and greater complexity. Jira here, Confluence there; deployment pipelines somewhere in between. The vision of a transparent, manageable flow process dissolved into a patchwork of data and tools. The Release Train Engineers (RTEs) – the coordinating linchpins of the SAFe model – were under increasing strain. Instead of solving problems, they were spending their days on manual data searches, inconsistent reporting, and endless analysis cycles. 

“RTEs should be steering – not chasing data. But chasing data had become their daily reality.” 

In short: it was a classic case of methodological ambition clashing with operational reality – the trigger for a radical reset. AgileTech needed an AI-driven solution that could structure data, restore oversight, and prepare decisions. 

The situation was precarious: the less valid data was available, the more often gut feeling replaced facts. Operational teams lost time, trust, and direction. And caught in the middle were the RTEs – doing damage control rather than steering. While drowning in data jungles, hopping between tools, and crunching Excel sheets, they left management with a “black box” view of the value stream. 

AgileTech pulled the emergency brake. That’s when we came in: tasked with building an intelligent assistant system that wouldn’t just aggregate but recognize patterns and thought ahead. A solution that wouldn’t simply reflect SAFe, but understand context –and restore the ability to act. 

Together with an interdisciplinary powerhouse of AI engineers, database architects, and front- and backend developers from X-INTEGRATE, IBM, and catworkx, AgileTech created a digital assistant that is far more than a reporting tool. Based on a standardized data model, all relevant system sources – from Jira to CI/CD pipelines – were harmonized. The outcome: a real-time dashboard that reveals patterns, highlights weaknesses, and makes team dynamics visible. In short: an intelligent sparring partner that analyzes retrospectively and reasons prospectively. 

At its core: an AI trained on the SAFe knowledge model, powered by IBM watsonx. It analyzes flow metrics such as Flow Time, Load, and Efficiency, identifies anomalies, and derives concrete recommendations for action. Access is provided via a text- and role-based chat interface – intuitive, context-aware, and seamlessly embedded in daily workflows. 

Since then, RTEs can finally breathe again. Instead of managing data, they can refocus on what matters: developing high-performing teams and steering successful releases. 

The results speak for themselves. Within a short time, average velocity increased by 25%, while flow time decreased by 30%. Reporting processes were automated. In sum, a massive efficiency gain that created room for strategic work. RTEs now have time to coach again, and decisions are once more based on valid data rather than intuition. 

Beyond this, the SAFe Assistant has established a platform that reaches far beyond this single use case: it is modular, extensible, and ready for AI-driven applications in areas such as controlling, HR, or production. 

The roadmap is set. Additional data sources are being connected, ML models for risk analysis integrated, and recommendations evaluated. With the SAFe Assistant, AgileTech is delivering not only operational relief but also an intelligent decision-making foundation for the entire organization: scalable, transparent, and future-ready. 

AgileTech has demonstrated how an organization can strengthen its own performance with smart technology – not through tools alone, but through the right interplay of methodology, data, and intelligence.