Hearing Aid Voice Control SDK
Digital hearing amplifier
How BotSurf works on a Hearing Aid
BotSurf runs on a Hearing Aid as an on-device AI voice agent, not a fixed list of matched commands. Voice TTS, audio enhancement, voice commands. Because the underlying engine is a real AI model rather than a command-matching layer, it handles phrasing variation, multi-step requests, and follow-up questions the way a person actually talks — not the rigid "say this exact phrase" pattern older voice integrations require.
The manufacturer opportunity
Hearing health market. This is a genuine AI differentiator, not a rebadged wake-word matcher — Hearing Aid manufacturers can market real on-device AI reasoning, multi-step task handling, and privacy-preserving local processing, positioning against competitors still shipping fixed-command "voice control" as if it were the same thing.
Hardware & memory baseline
The floor Medical & Healthcare devices need to clear before integration; exact figures are confirmed per project once we know your chipset and target markets.
Minimum RAM
2 GB for tablets and carts; 512 MB for simple connected devices (inhalers, pill dispensers) relaying to a companion app
Minimum storage
4 GB — clinical documentation templates and offline-cached patient data add real footprint beyond a consumer device baseline
CPU architecture
ARMv8/64-bit for tablets and carts running full AI-assisted documentation; simpler for single-purpose connected devices
Microphone array
Noise-robust 2+ mic array recommended — clinical environments have real background noise (monitors, other conversations) that single-mic pickup struggles with
Network
Hospital Wi-Fi or wired for EHR integration; on-device AI processing is the default posture here, minimizing what leaves the device at all
Regulatory note
BotGentz has not been independently audited against HIPAA or any medical device certification. The on-device processing and centralized admin architecture support an institution's own compliance program — the certification itself remains the manufacturer's and institution's responsibility
Chipset compatibility
Compatible with the ARM-based medical-grade tablet and cart platforms already common in clinical deployments
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