Articles on: Sustainability

Environmental Impact of Similia’s AI Features

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: Data centres use water for cooling while AI requests are processed. How much a feature uses depends on the task: a single search is a small request, while longer tasks such as AI Analysis or an AI Chat answer can involve many model requests. Training large models is more intensive, but Similia relies on pre‑trained models for analysis.
  • Infrastructure Choices: We use established cloud and AI providers rather than running our own servers. We don't choose regions or providers on environmental criteria.
  • Our Practice: Efficient coding and right‑sized scaling.
  • User Control: AI features only run when you use them. Avoiding AI features reduces compute usage further (see below).


Searching without AI


Repertory search uses Semantic (AI) search by default.


To switch to keyword search for now, open the search-type menu next to the repertory search box (a sparkle icon, labelled Semantic when there is room) and choose Keyword. This choice is not saved: search goes back to Semantic when you reload the page or reopen Similia.


To use keyword search permanently:


  1. Open Settings.
  2. Under Repertory & analysis, choose Work mode (the card is headed "How you find rubrics").
  3. Choose Manual.


Manual hides semantic search in the repertory and materia medica, Notes to Rubrics, AI Analysis, Analyze Photo, MM Rubrics and AI Chat, so you search by keyword only. The setting is saved to your account. Choose AI-assisted to bring the tools back.


Manual does not switch off every AI feature: Live Audio still transcribes (without the AI analysis), and tools such as Generate with AI in a case timeline run only when you choose them.

Updated on: 11/10/2026

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