Vobiz.ai: India’s Voice AI Backbone for Low-Latency Telecom

Bengaluru-based Vobiz.ai is spearheading the development of AI-first telephony infrastructure in India, addressing critical bottlenecks that hinder the scalable deployment of voice AI agents. Founded in 2025 by Suman Gandham and Vikash Srivastava, the startup is building the foundational layers necessary for robust AI-to-human communication, distinguishing itself in a rapidly evolving voice AI landscape.

While voice AI agents are gaining significant traction, existing telecom infrastructure was primarily designed for human-to-human interactions and traditional call centers. This legacy setup creates challenges such as high latency, inefficient routing, and issues with spam detection and call completion, which are becoming serious impediments for machine-scale conversational calls.

Vobiz.ai tackles this mismatch by providing programmable APIs, lower-latency routing, and AI-optimized media infrastructure. The platform is designed to sit underneath the voice AI stack, enabling enterprises to connect their AI agents to telecom networks more efficiently and reliably, rather than competing at the AI model layer itself.

Addressing Latency in Voice AI

The inspiration for Vobiz.ai stemmed from founder Suman Gandham’s earlier experiences within India’s startup ecosystem, including founding consumer neobank Finin, which was acquired by Open. During subsequent experiments with AI voice agents for BFSI use cases, Gandham identified that the primary bottleneck was not the AI models but the underlying telephony infrastructure.

This insight led Gandham to partner with Vikash Srivastava, who brought extensive experience from telecom infrastructure companies like Plivo and Bandwidth. Together, they recognized that traditional telecom infrastructure, introducing 300 to 500 milliseconds of delay, compounded by latency from speech-to-text (STT), text-to-speech (TTS), and large language model (LLM) inference layers, could lead to total response times exceeding 1.5 seconds, making AI interactions unnatural for humans.

Vobiz.ai’s solution involves a “single-hop” architecture engineered to significantly reduce delays, background noise, and overall latency. The platform integrates with multiple AI orchestration and speech providers, including OpenAI, Gemini, ElevenLabs, Cartesia, AWS Polly, and LiveKit, dynamically routing workloads based on performance, latency, language, and use case suitability.

Internally, Vobiz.ai leverages AI across its telecom infrastructure stack for various functions. These include real-time media optimisation, echo cancellation, noise suppression, packet routing optimisation, spam and answering-machine detection, AI-ready programmable call controls, and support for call streaming and transcription.

This optimization-first approach claims to reduce telephony latency to under 80 milliseconds at P95 levels. Furthermore, the startup emphasizes developer experience, allowing clients to complete KYC, provision numbers, access APIs, and deploy integrations through a self-serve onboarding flow within minutes, a significant departure from legacy telecom providers.

Market Traction and Business Model

Since its launch in November last year, Vobiz.ai has rapidly scaled its operations, growing from approximately 1 Lakh calls per month to more than 10 Lakh calls per day, while maintaining a customer retention rate of 98%. The initial wave of traction originated from India’s burgeoning voice AI startup ecosystem, with clients such as Bolna, Sarvam AI, Razorpay, RevRag, Smallest.ai, and Navana AI.

The company is observing a shift towards direct enterprise adoption, particularly across sectors like fintech, lending, insurtech, logistics, and real estate. Currently, enterprises account for roughly 30% of Vobiz.ai’s business, with AI voice startups contributing the remaining 70%. The founders anticipate enterprise adoption to surpass startup-driven demand by the end of the year.

Vobiz.ai operates on an infrastructure business model, projecting gross margins between 50% and 80%, depending on usage patterns and contract structures. Its revenue streams include telecom numbers, usage-based call billing, and value-added services such as transcription, call streaming, and answering-machine detection. Value-added services are expected to become the largest revenue contributor over time.

The startup positions itself as an infrastructure provider alongside global players like Twilio and Telnyx, and homegrown entities such as Exotel and Plivo. However, Vobiz.ai differentiates itself by being built specifically for AI-native workloads, unlike legacy systems designed for human communication. Vikash Srivastava noted the rarity of expertise combining telecom protocols, networking infrastructure, and modern cloud-native architectures.

Future Outlook and Global Expansion

Beyond its current focus on voice, Vobiz.ai is expanding into adjacent communication channels, including WhatsApp calling and chat integrations, with plans for SMS and RCS (rich communication service) infrastructure. The broader strategic goal is to become a default AI communication layer across multiple channels.

Geographically, Vobiz.ai is preparing for international expansion into markets including the US, Europe, Middle East, Africa, and Asia-Pacific. The founders intend to initially target regions where AI telecom infrastructure remains relatively underpenetrated, rather than directly competing in saturated markets. The platform has been designed around international compliance requirements, including DPDP, GDPR, SOC2, and ISO standards, according to Suman Gandham.

As enterprises increasingly transition from AI pilots to full-scale production deployments, the focus in voice AI is shifting towards infrastructure reliability, latency, scalability, compliance, and deployment complexity. This transition is expected to elevate the importance of the telecom layer, positioning Vobiz.ai to gain significant recognition.