Creating trust through transparency - How reev practices responsible AI

From product innovation to responsibility

From autonomously rectifying charging errors to optimizing the time and manner in which vehicles are charged, AI at reev is already delivering tangible added value for our customers. and customers.

Our Smart Recovery function is the industry’s first AI-powered self-healing function that is fully integrated into a holistic energy and charging management solution. It automatically detects and fixes faults at charging points, minimizing downtime and operational costs for charging infrastructure providers.

By analyzing error logs and device data, Smart Recovery identifies the cause of a malfunction and independently triggers corrective measures – which means that up to up to 30% of all detected faults can be rectified without manual intervention. This is a milestone for the electromobility industry.

At the same time, the reev electricity tariff combines dynamic electricity prices with AI-based optimization. Within the reev Platform, it automatically schedules charging processes based on real-time market prices and shifts energy consumption from expensive morning and evening hours to more cost-effective midday times. This intelligent load shifting can reduce energy procurement costs by up to 85% while contributing to grid stability and supporting the integration of renewable energy.

Our FIN AI Agent supports the reev customer support team by automating many routine requests and providing immediate, AI-based assistance.

For more complex or individual cases, customers can contact a human support specialist at any time. This ensures fast and reliable assistance – with empathy and a sense of responsibility at the heart of every interaction.

As with any AI-based system, performance depends on data quality and network conditions. We continuously monitor and refine our models to ensure reliability and transparency.

Together, these innovations show how reev uses AI responsibly to improve sustainability, efficiency and reliability – and how our principles for responsible AI guide every step, from product design to day-to-day operations.

In addition to these product innovations, AI also helps us to optimize customer communication, improve internal workflows and accelerate product development.

However, with this opportunity comes responsibility – to ensure that every algorithm, model and automation we use follows ethical, transparent and human-centered principles.

Our framework for responsible AI

To make this responsibility tangible, we have defined a framework based on seven guiding principles that apply to every AI use case at reev – regardless of whether it is a customer function or an internal tool.

• Fairness – We test data and model behavior for bias. Discrimination is not acceptable.
• Transparency – We communicate clearly where and how AI is used, especially when it influences people or decisions.
• Data protection and security – We protect all data. AI systems never disclose personal data or location data.
• Accountability – people remain responsible for the results of AI. Each system has an owner and an escalation path.
• Reliability – We test models under production-like conditions and monitor them for deviations or anomalies.
• Explainability – models must be understandable. We document logic, inputs and outputs.
• Supervision – A cross-functional AI committee reviews all AI initiatives that impact decisions, resources or user experience.

Each AI function is overseen by a responsible product owner who ensures human review and accountability.

These principles are set out in our AI checklist before implementation which every AI function – internal or external – must fulfill before release.

How we apply responsible AI in practice

Responsible AI is part of our daily operations – not a marketing label.

This is how it works in practice:

• Energy and load optimization: Our forecasting and load balancing algorithms are tested for accuracy, bias and explainability. Users can understand what influences each prediction.

• Internal tools: Even internal models – such as forecasting dashboards or AI-powered reporting – follow the same framework to ensure transparent, traceable decisions.

• Continuous learning: We train engineers, product managers and non-technical teams annually to revise RAI principles and update practices.

• Documentation and verification: Each AI function is logged, with its assumptions, test results and verification results documented and verifiable.

By integrating guidelines for the responsible use of AI into our workflows, we ensure that AI strengthens our mission: to enable sustainable, intelligent energy and charging management – without compromising accountability or data protection.

Continuous learning and shared responsibility

Responsible AI is not a one-off initiative – it is an evolving mindset. We regularly train our teams, review new regulations such as the EU AI Act and adapt our processes accordingly.

Trust in technology doesn’t come from algorithms – it comes from people. That’s why we invite partners and customers to engage with us, provide feedback and help shape an ethical, transparent AI future. Because only together can we ensure that AI remains what it should be: a tool for empowerment and sustainability.

“At reev, we believe that AI only adds value if it is trustworthy, explainable and human-centered. That’s why we have created a framework for responsible AI that ensures transparency, control and accountability at every step.”

— Alex Di Mango, CTO reev