Neural Machine Translation (NMT)
Deep learning models producing human-quality translations across 22+ Indian languages with domain-specific training for legal, medical, and technical contexts.
Transliteration
Cross-script conversion preserving pronunciation, enabling phonetic access and English keyboard typing for regional languages with intelligent mapping.
Text-to-Speech (TTS)
Natural-sounding audio synthesis with multiple voice profiles trained on native speakers, enabling accessibility for visually impaired users and audio learning.
Automatic Speech Recognition (ASR)
Real-time transcription trained on Indian accents and code-switching, enabling voice-based data entry, live captioning, and hands-free interaction.
Document Digitization & OCR
Advanced OCR trained in Indic scripts converts legacy documents into machine-readable text, enabling all translation and speech capabilities.
Linguistic Diversity
22 official languages, 6,000+ dialects, 55+ languages with 1M+ speakers create fragmented communication.
Neural models trained across all major Indic languages with domain-specific accuracy.
Information Trapped
Critical legal judgments, medical records, and government documents remain locked in English or single languages.
Document digitization and translation at scale - 22M+ documents already processed.
Generic Tools Fail
General-purpose translators lack domain vocabulary, miss context, and destroy document formatting.
Domain-specific training preserves legal, medical, technical terminology with formatting.
Accessibility Gap
Text-only interfaces exclude visually impaired users, literacy-challenged populations, and hands-free contexts.
Voice interfaces with TTS and ASR enable natural interaction in any Indian language.

