Eka Care has unveiled Parrotlet, an advanced AI-powered clinical speech model built specifically for accurate, context-aware medical transcription in Indian healthcare settings. The model excels at understanding diverse Indian accents, medical terminology, multilingual consultations, and noisy environments—delivering faster, more reliable documentation for doctors while reducing manual typing and administrative burden.
Glimpse:
Parrotlet processes doctor-patient conversations in real time, converting speech to structured clinical notes with high accuracy across Hindi, English, regional languages, and mixed-language dialogues. Trained on millions of anonymized Indian clinical interactions, it handles abbreviations, drug names, symptoms, and diagnoses with contextual intelligence. The launch positions Eka Care to transform clinical workflows in busy OPDs, hospitals, and telemedicine platforms by minimizing errors and freeing physicians to focus on patients.
Eka Care, a leading digital health platform in India, has introduced Parrotlet—an indigenous clinical speech recognition model designed exclusively for the complexities of Indian medical consultations. Unveiled in early 2026, Parrotlet addresses longstanding challenges in voice-based documentation: heavy accents, code-switching between English and regional languages, background noise in crowded OPDs, and specialized medical vocabulary.
Key capabilities of Parrotlet include: Multilingual & accent-robust transcription — supporting Hindi, English, Tamil, Telugu, Bengali, Marathi, Kannada, and mixed-language conversations common in India Clinical context understanding accurately capturing symptoms, past history, drug names (including generics and brands), dosages, diagnoses, and follow-up instructions Noise-resilient performance reliable even in busy clinics, hospital wards, or home settings Structured output generation converting free-form speech into SOAP-format notes, prescription drafts, discharge summaries, or referral letters Integration-ready plugs into Eka Care’s EHR platform, ABDM-compliant systems, and third-party apps via APIs
The model was trained on a massive, anonymized corpus of real Indian doctor-patient interactions, ensuring relevance to local epidemiology, slang, and consultation styles. Early pilots in multi-specialty hospitals and urban clinics have shown 90%+ accuracy on complex consultations and up to 70% reduction in documentation time.
Eka Care emphasized that Parrotlet prioritizes privacy (on-device processing options), clinician review workflows (human-in-the-loop), and compliance with DPDP Act and ABDM standards. The company plans phased rollout starting with Eka Care users, followed by open API access for hospitals and telemedicine providers.
This launch strengthens India’s growing ecosystem of home-grown clinical AI tools, directly tackling one of the biggest pain points for overburdened physicians: documentation overload.
“Parrotlet listens like an Indian doctor and writes like a perfect scribe so clinicians can finally spend more time healing and less time typing.”
By
HB Team
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