Voice AI & NLP

Hindi, Hinglish, and English are supported natively with custom-trained models. For 20+ additional languages, we use Whisper large-v3 with domain-specific fine-tuning. We also handle code-switching (mixing languages mid-sentence), which is common in Indian business contexts.

95%+ accuracy for trained domains, measured on real-world audio (not clean lab recordings). We achieve this through domain-specific vocabulary training, accent adaptation, and confidence scoring. Low-confidence transcriptions trigger clarification prompts rather than incorrect actions.

Yes — our pipeline includes adaptive noise cancellation, voice activity detection, and confidence scoring. In noisy environments like hotel lobbies or factory floors, we combine noise filtering with confirmation prompts for low-confidence commands. RunHotel processes voice commands reliably in busy hotel reception areas.

We fine-tune speech recognition models on your target demographics. For Indian markets, we train on Hindi, Hinglish, and regional accent variations. For global deployments, we support 50+ languages with accent-aware models. Accuracy improves over time as the system learns from real usage patterns.

Yes — we offer on-device speech recognition using optimized Whisper models and local NLP pipelines. Offline mode handles core commands with slightly reduced accuracy compared to cloud. For hybrid setups, the system processes locally when offline and syncs with cloud models when connectivity returns. Ideal for field workers, remote sites, and areas with unreliable internet.