AI voice agents in English and Urdu

A voice agent is a chain of systems that has to work in real time, because callers notice even short pauses:

• Telephony: the call arrives over SIP and is answered by a switch such as FreeSWITCH.
• Speech-to-text: the caller's audio is transcribed, for example with Faster-Whisper.
• Understanding: the agent works out what the caller wants and looks up the answer in your systems.
• Text-to-speech: the reply is spoken back in a natural voice, for example with Coqui XTTS.
• Logging: the conversation, outcome and any hand-off are recorded for review and analytics.

Voice agents do well on frequent, predictable calls: timings and schedules, booking status, opening hours, simple bookings and reminders. They are a poor fit for complaints, sensitive situations and anything that needs judgement or negotiation. A good design answers the routine calls and passes the rest to a person quickly, with the context already captured.

Callers should also always be able to reach a person by asking for one, and the agent should say clearly that it is automated. Those two rules do more for caller trust than any choice of voice.

Many callers in Pakistan switch between Urdu and English in the same sentence. A voice agent for that audience has to be designed and tested for mixed speech, local names, place names and numbers, not just for clean textbook Urdu. That bilingual design is at the centre of the AI Voice Operations platform.

Both approaches work. The choice depends mostly on data rules, call volume and in-house skills.

Share the most common reasons people call you, any existing call scripts or sample recordings, the languages involved, your current telephony provider and the systems the agent needs to read from. From that you get a written scope covering call flows, integrations and the escalation path, with a fixed quote.