Scalable AI. Purposeful innovation.
We believe AI innovation and environmental efficiency go hand in hand. By optimizing our digital infrastructure and sourcing certified renewable energy, we deliver world-class AI that respects the resources we share.
Navigating the energy demands of AI
AI brings immense value, but its growth requires significant computational power. Training and running high‑performance models consume electricity and water resources we are committed to using wisely through technical efficiency and transparent sourcing, so our impact stays in line with our responsibilities.
We integrate environmental standards into our daily operations — not just to meet regulations, but because we care about the legacy of the tools we build. From the code we write to the offices we share, we’re making sustainability a natural part of how DeepL grows.
Renewable energy for data centers and offices
We prioritize renewable energy in our operations. Our policy is to select headquarters and data centers that offer renewable electricity options, and we are actively working toward 100% renewable sourcing across our primary facilities. We monitor our electricity usage (Scope 2) to ensure our growth remains as efficient as possible.
Digital & operational efficiency
We minimize our digital footprint through neural network optimization, reducing the computational cost of every translation. Beyond our code, our teams carry this mindset into our offices, applying energy‑saving protocols that lower our operational energy demand and make efficiency a shared priority across the company.
A culture of efficiency
We integrate sustainability into our daily workflows, making resource-aware choices a natural part of our development and operations. By providing the right tools and training, we enable our teams to drive our transition toward a lower-carbon model.
Sustainable travel incentives
We’ve made public transportation the first choice for business travel, prioritizing the lowest‑carbon routes wherever possible. To support sustainable daily habits, we subsidize public transit passes and cycle‑to‑work schemes at selected global offices, helping employees commute with a lighter footprint.
Measuring our carbon footprint
Accountability requires data. We maintain a Greenhouse Gas (GHG) inventory to track emissions across our operations and value chain, following the GHG Protocol Corporate Standard.
Emissions are divided into three categories:
- Scope 1 (Direct operations): Negligible impact. We operate a digital-first model with no vehicle fleet or onsite combustion.
- Scope 2 (Purchased energy): Our primary focus. Covers electricity and heating for our headquarters and managed data centers.
- Scope 3 (Value chain): Wider impact. Includes indirect emissions from across our ecosystem (Cat 1-3, 5-8).
Inside our energy-efficient data centers
Discover how our partnership with pioneering sites like EcoDataCenter allows us to scale our AI while maintaining a low carbon footprint.
Driving change together
Are you interested in how DeepL balances high-performance innovation with resource efficiency? Connect with our team to learn more about our data-driven approach to responsible AI.
