CT earns EcoVadis Silver Medal for sustainability, ranking among the top 9% in the industry.

This prestigious recognition places CT among the top 9% of companies globally within its industry, as assessed by EcoVadis, a leading authority in business sustainability ratings.

News

26 Sep 2024

CT proudly announces that it has been awarded the EcoVadis Silver Medal, a testament to the company’s dedication to sustainability. This prestigious recognition places CT among the top 9% of companies globally within its industry, as assessed by EcoVadis, a leading authority in business sustainability ratings.

The EcoVadis evaluation covers four key areas: environmental impact, labor and human rights, ethics, and sustainable procurement. The rigorous assessment process reflects CT’s commitment to establishing and maintaining strong management practices in these crucial areas.

In addition, EcoVadis has recognized CT as a Leader in Greenhouse Gas (GHG) Management, acknowledging the company’s proactive efforts to reduce emissions and positively impact the environment.

This accolade reinforces CT’s ongoing commitment to sustainability, which is central to the company’s business strategy. Looking ahead, CT will continue to invest in sustainable technologies and practices, with a focus on further reducing its carbon footprint, enhancing supply chain transparency, and integrating eco-friendly solutions across its operations. These initiatives align with CT’s strategic vision of becoming a leader in environmental stewardship and responsible business growth.

Related News

News

CT has presented the groundbreaking AWES Industry Centre of Excellence in La Gomera at a prominent event to promote R&D+i projects on the island.

Read more
News

EcoMobility: CT develops predictive digital twin for road traffic in smart cities.

Using machine learning technology, the CT team trains decision-making models for vehicles and people, allowing the digital twin to autonomously make decisions in real time, as if it were a human mind.

Read more
News

CT has completed the IADGENOL project on automating AWE System trajectories using deep learning.

After two years of research, CT has successfully developed a Deep Learning-based control model that addresses the dynamic challenges of autonomous AWE system operations. In collaboration with Carlos III University of Madrid, CT showcased the results of the latest validation tests in a simulation environment for the AWES control system at the European AWES Congress, AWEC2024, in Madrid, demonstrating precise wind alignment and optimal energy generation trajectories.

Read more