Why Raiqon AI Started With Codebeamer, and Why This Benefits Every Product Organization

Product companies are accelerating their adoption of AI. For Codebeamer users, the situation is uniquely attractive: the most advanced AI for Codebeamer has already been on the market for two years. The story gets even better. The experience gained from building this first integration now benefits companies working with any ALM or engineering toolchain.

Deep Expertise in Both Codebeamer and AI

Raiqon AI was founded by the original creators of Codebeamer, including Szabi and Janos Koppany. Their background gives them a deep understanding of the platform, the market and the needs of complex product organizations. The team also includes Geza Velkey, an experienced research engineer with Silicon Valley experience who previously worked with Codebeamer as a product owner.

We built Raiqon with the same philosophy that guided the early days of Codebeamer: a small, exceptional team that understands engineers and solves real problems fast.

Szab Koppany

This combination of domain knowledge, tool expertise and AI engineering set the stage for the first production-grade AI integration for Codebeamer.

Codebeamer as a Strong Platform for AI

Successful AI adoption in product development depends on usability. Engineers want to stay inside their existing tool and avoid context switching. Codebeamer is well suited for this. Its extensibility, plugin model and integration flexibility made it a strong first target for an AI platform focused on regulated product development.

Because the Raiqon team already understood Codebeamer’s internals, they could implement AI capabilities quickly and react to early customer feedback much faster than typical enterprise integration projects.

Research-Backed Development

Raiqon’s development approach has always been grounded in practical research. The KIMBA project provided a framework for working with academic partners and industry leaders. Organizations such as BMW and Schaeffler participated in this research context, shaping requirements and validating use cases around traceability, verification support and AI-assisted systems engineering.

With this foundation, Raiqon demonstrated how AI can deliver measurable productivity gains for companies building complex, regulated products.

“We used to work with an external service provider, which led to two to three months elapsed time for reviews. With Raiqon, we shortened this to one to two weeks.”

— Martin G., Lead Systems Engineer, OEM

These results show the real value of combining Codebeamer’s flexibility with a domain-specific AI designed for engineered systems.

A Platform for More Integrations

Starting with Codebeamer created a robust baseline for expanding into other environments. The Raiqon platform now extends towards DOORS Next, Jira, SmartGit, Polarion and additional tools used across the V-model and the broader product lifecycle.

This means organizations do not need to standardize on a single tool to benefit from consistent AI-driven engineering workflows.

What This Means for You

Even if your organization does not use Codebeamer, you gain from the experience Raiqon collected during the first integration. The platform’s architecture, data handling, review workflows and AI reasoning were refined in a demanding environment. As a result, Raiqon delivers high ROI regardless of the tools you use.

Conclusion and Next Steps

Raiqon AI demonstrates how AI can meaningfully accelerate product development when it is grounded in deep tool knowledge and real customer feedback. Codebeamer was the ideal starting point, but the benefits extend to the entire ecosystem of modern engineering tools.

If you want to explore what AI for Codebeamer or AI for your engineering toolchain can deliver, visit the resource hub or request a demo.