Yes, in production, across 10 or more Indian languages plus Hinglish, running more than 1 million calls a day. That's not a lab demo number; that's live volume on collections, renewals and retention calls where a wrong word or a missed dialect shift costs you the conversation.
Why this is a fair question
The reason this is a fair question is that most voice AI gets built and tested on English, then bolted onto Indian languages as an afterthought. It shows immediately on a real call: traffic noise, a bad line, code-switching mid-sentence between Hindi and English, regional dialect variation within the same language. Generic speech recognition breaks on exactly the conditions an Indian contact centre deals with every day.
Eight years of Indic interaction data
What makes the difference is eight years of real Indic contact-centre interaction data behind the model, not a general-purpose speech layer retrofitted for India. The speech components themselves are vendor-agnostic and swappable if a client needs a specific voice; the actual moat is the outcome layer built on years of hearing how Indian customers actually talk on a collections or retention call, including the parts that don't sound like a textbook.
The honest caveat
This isn't about claiming perfect accuracy on every accent in every state. It's that the system is trained on the hardest version of the problem, adversarial customers, patchy telephony, heavy code-switching, rather than a clean-room version of it. If it holds up here, the easier markets aren't a stretch.
Frequently asked questions
Does AI actually work for collections calls across Indic languages?
Yes, in production, across 10 or more Indian languages plus Hinglish, running more than 1 million calls a day on collections, renewals and retention.
Which languages are live in production?
10 or more Indian languages plus Hinglish are in production. Arabic, South-East Asian and European languages are also available, and a new language typically takes four to six weeks to add.
Does Oriserve build its own speech recognition?
No. The speech components are third-party and deliberately vendor-agnostic, so they can be swapped when a client mandates a specific voice or vendor. The defensible layer is above the speech: eight years of real Indic contact-centre interaction data and the outcome layer built on it.
What about code-switching between Hindi and English mid-sentence?
That is the normal case rather than the edge case on an Indian contact-centre call, and it is one of the conditions the models are trained on, along with traffic noise, poor line quality and regional dialect variation within the same language.