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VERBUND faces rapidly increasing, highly complex requirements for sustainability reporting and ratings, further intensified by new and evolving EU regulations (e.g. CSRD). Manual processes and reliance on external consulting are time-consuming, costly, hard to scale, and prone to errors.

We are looking for an innovative solution, ideally an AI-powered platform, that automates report and rating submissions, integrates data from internal and external systems, interprets complex ESG standards and EU regulatory requirements, enables AI-assisted report generation and benchmarking, and actively supports employees in navigating regulatory complexity.
The goal is efficient, consistent, audit-proof and EU-compliant reporting that reduces costs, enables rapid benchmarking, keeps pace with regulatory change, and minimizes compliance risks. Startups with expertise in AI-driven reporting, regulatory intelligence or ESG reporting solutions are invited to apply.

VERBUND faces growing and complex cyber security requirements in OT and IT environments. Manual SOC and incident response processes are time-consuming and resource-intensive.
We are looking for an innovative solution (e.g., a modular platform with artificial intelligence) that automatically detects threats, prioritizes alerts, correlates OT/IT data across system boundaries, suggests adaptive countermeasures, and supports employees in incident response and data classification.

The goal is efficient, consistent, and scalable cybersecurity that reduces the workload on SOC teams, shortens response times, detects complex attack patterns, and reliably protects critical infrastructure. Startups with expertise in AI, anomaly detection, automated security workflows, or OT/IT security analytics are invited to apply.

In many electric truck fleets, transport management systems (TMS), charge point management systems (CPMS), and energy management systems (EMS) operate in parallel without a smooth integration. This is especially critical in heavy-duty truck charging, where high power demand, strict operational schedules, and grid constraints collide. The lack of integration leads to conflicts between route and dispatch planning, charging schedules, grid limits, and safety requirements, resulting in inefficiencies, higher energy and infrastructure costs, missed operational targets, and increasing system complexity.
We are looking for an innovative solution, such as an intelligent middleware or orchestration layer, that enables integration of TMS (logistics & deadlines), CPMS (charging execution) and EMS. The goal is reliable, intelligent, grid-friendly, and cost-optimized truck fleet charging, ensuring that operational constraints (e.g. required state of charge by a given departure time) are met while respecting grid limits and energy price signals. The solution should provide a scalable and future-proof foundation for advanced use cases such as depot-level optimization, peak shaving, renewable assets integration, and vehicle-to-grid for heavy-duty vehicles.

Axpo is exploring solutions that combine fast-charging stations with battery storage and other on-site energy assets to enable intelligent intergration, control & monitoring. A comprehensive load management solution would enable optimized use of the charging infrastructure, especially in logistics and transport applications with electric trucks. Battery-backed fast charging addresses several structural challenges faced by customers. Grid connections often cannot be sufficiently expanded due to limited capacity provided by distribution system operators, which restricts achievable charging power. At the same time, fast-charging stations create high power peaks, leading to increased electricity procurement costs. In addition, photovoltaic generation cannot be optimally used, as energy production does not align with the times when trucks need to be charged.
We are looking for market-ready or near-market solutions that integrate batteries with fast-charging infrastructure and enable intelligent charging strategies. Batteries should be used to store energy and release it during high-power charging sessions, allowing charging at higher power levels despite grid limitations, while charging the battery itself can take place more slowly based on station utilization. The solution should ensure that electric trucks are fully charged by the next operational day, which is critical for logistics operators running 5–7 days per week. The goal is to develop or further validate a product combining fast-charging stations and battery storage, supported by intelligent control logic, ideally demonstrated in a real-world pilot project. Startups offering software-driven or hybrid (software + hardware) solutions for battery-buffered fast charging or load management in logistics depots are invited to apply.

SMATRICS EnBW manages charging infrastructure, including a wide range of associated assets and services such as peripheral infrastructure, maintenance, and site operations. Each site involves different asset configurations, contract types, and revenue models, resulting in high operational complexity.
Today, this complexity is handled largely through manual, Excel-based processes that lack transparency, auditability, and scalability. Complex contract logic, conditional clauses, and site changes (e.g. expansion or rollback) are difficult to track and manage reliably.
We are looking for a software-based solution that enables structured management of assets, contracts, and revenues across charging sites. The solution should support complex contract logic, ensure revision-safe histories, automate recurring reporting, and provide transparency for stakeholders. The goal is to replace manual workflows with a scalable, audit-ready platform that increases efficiency and enables future growth.