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🔧 How It Works

Real-time interpretation. Native-level understanding. No subtitles. No lag.

🎙 Speak in any language — hear your own

InterMind is a multi-user video conferencing platform with instant, bidirectional interpretation. Each participant can speak in their own native language — at any time — and hear everyone else in their chosen language.

No need to wait for turns or rely on subtitles.

🧠 Real-time translation powered by deep context

Behind the scenes:

  1. Speech-to-text: Every voice input is transcribed live.
  2. Neural translation: Transcripts are translated into your native language — with tone and intent preserved.
  3. Voice synthesis: The translated message is spoken in real time, using your voice settings.

All this happens with a latency under 3 seconds — equivalent to a human simultaneous interpreter[1] [2].

📈 Better than human — and improving every day

InterMind enables seamless integration with leading LLM providers — selected based on your chosen privacy region. We don’t train our own models, but we fine-tune interpretation settings using real-world multilingual meetings to ensure relevance and clarity.

🧩 Deep memory = deep understanding

Unlike generic translators, InterMind remembers your meetings:

  • Context of prior conversations
  • Agendas, participants, project-specific terms
  • Outcomes, tasks, and decisions

Your AI interpreter evolves with your team. It understands not just the language — but the topic, project, and personalities involved.

Confidentiality is always your choice.

🔐 Privacy by Design

Use Region-Segmented Privacy Architecture to decide where and how your data is processed.

  • Turn memory on/off at any time
  • Wipe AI memory after meetings
  • Select privacy zones (US, EU, Asia) for regulatory compliance

All audio/video routing is handled by our proprietary Mind API, built in-house to ensure performance and data sovereignty.


  1. Industry benchmark for real-time human interpretation latency is ~2–3 seconds. ↩︎

  2. Based on current progress in AI interpretation, we expect that within 2–3 years, models will consistently outperform top-tier human interpreters — including in specialized domains like law, finance, healthcare, and engineering. ↩︎