The full stack — fine-tuned Indic models, GPU infrastructure with universities and government, and an agentic layer that cuts inference cost up to 75%.
Six layers. Most never call a model — it lives at the leaf, one cheap call at a time. That discipline is the moat.
Keep the expensive call at the leaf, and the AI Tutor teaches any topic at 80% lower cost than calling a model every turn.
Owned in India. Tuned on Indian data. Built for Indian institutions — from compute all the way to the application.
Enterprise & government models, fine-tuned on Sarvam and the IIT LLMs.
Compute with universities and government — data stays within India.
Our 7B-parameter Indic SLM, being fine-tuned on India's open-source foundation models.
Low-latency speech models, tuned for Indian accents and languages.
Two platforms, live on the Neobound stack.
Higher Education
Drona gives every institution a private, sovereign platform — where faculty teach and students learn, grounded in the university's own curriculum, semester and exams.
from bolcho import VoiceAgent agent = VoiceAgent( model = "bolcho-indic", voice = "asha", language = "hi-IN", telephony = True, ) agent.on_call("+91XXXXXXXXXX") # STT + LLM + TTS, wired & live
Voice AI
A full-stack voice AI platform to build and run agents across every channel — fast, reliable and affordable.
We partner, fine-tune and deploy sovereign models into production.
In India, we solve Indic problems — on our own data, language and compute. So we build the full stack to beat the real constraint: power and inference cost.
Data, models and compute stay within India's control.
The agentic layer calls a model only when it has to.
Education, healthcare and governance — what matters.
Enterprise, university or government — deploy Indic models and agentic apps that are fast, affordable and sovereign.