Google Cloud and Randstad Digital Deploy Agentic AI at Forze Hydrogen Racing

Knowledge loss during high workforce turnover is a critical operational risk. Google Cloud and Randstad Digital demonstrate how agentic AI converts fragmented institutional data into actionable intelligence.

Every year, the Forze Hydrogen Racing team experiences a 100% workforce turnover, onboarding 50 to 60 new student engineers who must immediately resume complex hydrogen-electric racing car projects. After 18 years of iteration, the team's technical DNA—specifications, CAD drawings, telemetry, and operational guidelines—had become siloed across thousands of documents on multiple platforms, creating steep learning curves and dependence on alumni for repetitive foundational queries.

What was announced

Google Cloud announced a collaboration with Randstad Digital to deploy Forze Mirate, an agentic AI solution for Forze Hydrogen Racing. Built natively on Google Cloud's secure infrastructure and powered by Gemini Enterprise and Gemini models, the AI agent synthesizes decentralized historical data into a conversational interface delivering real-time, role-specific insights with citations.

Since deployment, Forze Hydrogen Racing reports concrete operational gains: time-to-productivity for new engineers reduced by up to three times, reliance on alumni and lead engineers cut by 80%, and institutional knowledge retention improved by 50%.

Forze Mirate is a testament to how agentic AI can seamlessly integrate into the flow of work to drive tangible business outcomes. By building on Gemini Enterprise, Randstad Digital has created a highly secure, grounded solution that translates complex, siloed data into actionable intelligence.

Why this matters

For CIOs, CISOs, and IT directors, Forze Hydrogen Racing is a concentrated version of an enterprise-wide challenge: preserving institutional knowledge during talent transitions. With attrition, restructuring, and retirements driving knowledge loss across regulated industries, agentic AI grounded in proprietary data offers a defensible blueprint for continuity, audit-ready citations, and accelerated workforce ramp-up—without compromising security or governance.

Technical details

• Foundation: Built natively on Google Cloud with Gemini Enterprise and Gemini models.
• Natural language queries: Engineers query 18 years of engineering history conversationally.
• Grounded answers: Responses include citations to original documents and alumni insights.
• Multimodal input: Engineers can upload photos of complex wiring and receive relevant specifications and safety instructions.
• Role-specific context: Output is contextualized to the engineer's task and role.
• Measured impact: 3x faster onboarding, 80% lower reliance on alumni, 50% better knowledge retention.

Softprom and Google

Softprom is the official partner of Google. Organizations seeking to deploy Gemini Enterprise, agentic AI workflows, and Google Cloud's AI stack can engage Softprom for licensing, architecture guidance, and implementation support.

This content was prepared as part of the Softprom DistriFlow project — an automated system for monitoring and adapting vendor news. Original source: original article.