SAID
Speech AI On Demand
An offline-first, real-time translation platform that breaks language barriers in the environments where it matters most — hospital rooms, forward operating bases, and emergency response scenes. No internet required. 100+ languages. Instant.
The Problem
In healthcare and defense environments, communication failures aren't inconveniences — they're life-threatening. A nurse who can't understand a patient's symptoms. A field operative who needs real-time intelligence in a language they don't speak. An emergency responder arriving at a scene where no one speaks English.
Existing translation tools require constant internet connectivity, introduce latency that makes real-time conversation impossible, and route sensitive data through third-party cloud servers — a non-starter for HIPAA-regulated healthcare and classified defense operations.
The Approach
We built SAID from the ground up as an offline-first architecture. The entire translation engine runs on-device — no cloud dependency, no data leaving the device, no connectivity requirements. This wasn't a feature bolt-on; it was the foundational design constraint.
- On-device speech recognition and translation models optimized for mobile and edge hardware
- Support for 100+ languages with medical and tactical terminology packs
- Real-time voice-to-voice translation with sub-second latency
- Document translation engine capable of processing complex RFPs and medical records
- Heads-up display integration for field operatives
- HIPAA-compliant data handling — zero cloud transmission of patient data
Architecture Decisions
The core challenge was fitting production-grade translation models into a package that runs entirely on consumer hardware. We made several key decisions:
- Model distillation — compressed large translation models to run within mobile memory constraints without sacrificing accuracy on critical medical and defense terminology
- Offline-first sync — language packs download once and update opportunistically, so the system works indefinitely without connectivity
- Cross-platform native — built for iOS, Android, and desktop with shared core logic and platform-native UIs
- Co-pilot mode — extended beyond translation to include AI-assisted document processing and RFP response generation
The Outcome
SAID moved from concept to production in under 12 months. The platform completed beta testing in September 2025 and secured its first commercial contract for real-time translation services. The system was presented to over 1,200 federal attendees at the U.S. Department of Health and Human Services, generating follow-up interest for additional deployment sessions.