PORTFOLIO

Today’s industrial automation is fragmented, each hardware vendor uses distinct programming environments, making automation costly, error-prone, and accessible only to large corporations. Around $80 billion are spent each year solely on hardware–software integration, and the top 500 manufacturers lose $1.4 trillion annually due to downtime largely caused by untested or buggy code. Meanwhile, there remains an $800 billion opportunity to automate processes that are currently untapped, largely due to a lack of expertise, especially within SMEs and legacy systems that are too difficult to update. Forgis addresses this by introducing a hardware-agnostic AI software layer that abstracts vendor differences, automatically generates native robot and PLC code, simulates operations, and validates performance before deployment. The result: up to 90% faster programming, 80% lower integration costs, and 80% of errors caught pre-deployment. This innovation triggers the same interoperability moment for industrial automation that Windows created for personal computing. By democratizing automation, Forgis enables SMEs to automate competitively, supports reshoring, and reduces CO emissions by cutting dependence on global supply chains.

Forgis is currently transitioning from validated prototype to an industry-grade solution, verticalized on specific applications. While we have achieved promising technical validation and strong early traction - such as pilot projects, PoCs, and measurable improvements in robot programming accuracy - the product still requires rigorous testing under industrial-grade conditions to meet the reliability and safety standards expected by clients. The main objective of the InnoBooster project is to specialize and mature the existing Forgis platform into an industry-grade solution tailored to the battery assembly application. The InnoBooster project focuses on validating the system across multiple robots and hardware setups to ensure reliability, safety, and scalability. From late 2025 to 2026, Forgis will conduct extensive testing with ABB and KUKA robots, targeting at least three proof-of-concept implementations to further validate the technology. In collaboration with industry partners, the project will deliver an industry-ready platform for large-scale deployment and commercialization.