Gupshup, the conversational-engagement platform best known for powering business messaging on WhatsApp, RCS and SMS, has launched a self-serve Voice AI Platform aimed at extending that engagement layer into live customer phone calls.
The no-code platform allows businesses to configure voice agents, build knowledge bases, design conversational workflows, set behavioural guardrails, run pre-launch simulations and monitor live performance through transcripts, analytics and testing tools — without requiring dedicated engineering resources for each new use case.
Use cases supported by the platform span sales and lead qualification, customer support, appointment scheduling, know-your-customer verification and payment reminders — functions that, across large consumer businesses, still typically rely on outsourced call centres or in-house teams handling repetitive, script-driven conversations at significant labour cost.
The platform supports both traditional telephony (PSTN) and WhatsApp voice channels, can be deployed on-premise or in the cloud, and is compatible with multiple speech-to-text, text-to-speech and large language model providers — a deliberately provider-agnostic architecture that lets enterprise customers avoid being locked into a single underlying AI vendor as the voice-AI landscape continues to evolve rapidly.
Gupshup has set an entry price point of $0.035 per minute, with new users receiving 100 free minutes to trial the platform — a pricing structure designed to lower the barrier to experimentation for businesses uncertain whether voice AI can reliably handle a given use case before committing to a larger deployment.
The launch positions Gupshup more directly against a growing field of voice-AI specialists competing for enterprise contact-centre budgets, but the company's existing distribution across WhatsApp Business messaging gives it a potential advantage: many of its current messaging customers are natural candidates to extend the same conversational infrastructure into voice without switching vendors entirely.
As enterprises across India and emerging markets look to control customer-service costs while maintaining — or improving — response quality, self-serve voice AI platforms represent one of the more concrete near-term applications of large language models in business operations. Whether Gupshup's bet pays off will depend on how convincingly its voice agents can handle the messiness of real customer conversations, where accents, interruptions and ambiguous requests routinely trip up systems that perform well in controlled demonstrations.
