Environmental Impact of Similia’s AI Features

Users sometimes ask about the environmental impact of AI features (energy use, water for cooling).

• Energy Usage: AI functions run on modern, efficient cloud infrastructure; major providers increasingly use renewable energy or offsets.
• Water Consumption: Inference uses tiny amounts of water per query for cooling (on the order of a fraction of a milliliter). Training large models is more intensive, but Similia relies on pre‑trained models for analysis.
• Infrastructure Choices: We partner with providers pursuing carbon‑negative and water‑positive goals and choose greener regions when feasible.
• Our Practice: Efficient coding, right‑sized scaling, and exploring offsets as we grow.
• User Control: AI features only run when you use them. Avoiding AI features reduces compute usage further.

As we grow, we plan to publish more concrete metrics and formalize environmental commitments.

Updated on: 18/09/2025