Diwakar Set, CEO of Tunk.ai, embarked on a market discovery mission. Not with a sales pitch, but with a listening ear. In meetings with CTOs and VPs across India’s contact center, fintech, and healthcare sectors, he deployed a simple strategy: demo the core speech-to-tech technology, then observe the unmet needs bubbling to the surface.

The pattern emerged quickly. A healthtech leader articulated their vision for fully automated lab test scheduling. Not as a cost play, but to achieve operational velocity and error-free consistency at scale.
Similar pain points echoed across industries:
The Talent Trap: Skyrocketing attrition (45%+ in Indian BPOs) and 30% wage inflation for competent agents.
Experience Erosion: More than half of customers still demanding human agents despite IVR investments.
Empathy Deficit: Only 1 in 5 support hires demonstrating genuine customer-centric behaviors.

During a pivotal whiteboarding session with Himanshu Sagar, Tunk.ai’s CTO, the breakthrough emerged. Himanshu asked, “What if we architect voice agents that don’t just process requests, but mirror human emotional intelligence?”

His hypothesis was bold. Could AI master the nuances of:
Tonal Adaptation: Shifting from assertive to reassuring based on vocal biomarkers?
Contextual Switching: Fluent transitions between Hindi, Tamil, and English mid-dialogue?
Pace Modulation: Automatically adjusting speech rhythm for elderly users versus Gen-Z callers?

Validation came swiftly. In executive roundtables, majority of leaders prioritized empathetic automation over pure cost reduction. The market had spoken. The future wasn’t about replacing humans, but augmenting them with AI that could scale the human touch.

Tunk.ai’s Agentic Voice AI was born from this insight. Not as another conversational AI platform, but as an emotional intelligence layer for enterprise communications. The lesson? Sometimes disruption starts not with a product demo, but with a simple question: What does your team wish our technology could truly understand?

In today’s hyperconnected digital landscape, customer expectations have reached unprecedented heights. A staggering 90% of service professionals confirm that voice calls remain the preferred channel for resolving complex issues – a surprising statistic in an era dominated by chatbots and messaging apps.

Yet traditional Interactive Voice Response (IVR) systems, with their endless menu trees and robotic tones, have become a source of widespread customer frustration. This glaring disconnect between consumer preferences and outdated technology has created the perfect storm for Voice AI agents to emerge as the next evolutionary leap in customer service.

Agentic AI represents a fundamental shift from reactive to proactive artificial intelligence. Unlike conventional AI assistants constrained by predetermined scripts, these systems demonstrate remarkable autonomy – think of them as digital concierges that don’t just respond to requests but anticipate needs.

Modern agentic AI can:
Dynamically replan business trips when flights get canceled, automatically rebooking hotels and transportation.
Proactively monitor elderly patients’ vital signs, adjusting medication reminders based on real-time health data.
Predict supply chain disruptions and autonomously reroute shipments before human managers spot the issue.

This proactive capability stems from sophisticated neural networks that continuously analyze patterns, learn from interactions, and make judgment calls – all while maintaining full audit trails for human oversight.

Today’s most advanced Voice AI agents combine several groundbreaking technologies:
Emotion-aware processing that detects subtle vocal cues like tone, pitch, and speech patterns to gauge customer sentiment.
Contextual memory that maintains conversation history across multiple sessions.
Real-time translation enabling seamless multilingual support without latency.

Leading implementations are achieving what was once thought impossible:
A major European bank reduced call abandonment rates by 63% after deploying emotion-sensitive voice agents.
A healthcare provider automated 89% of routine appointment scheduling while maintaining 4.8/5 patient satisfaction scores.
An e-commerce giant handles 12 million monthly voice queries with resolution times under 90 seconds.

While the potential is enormous, successful deployment requires addressing key hurdles:
Accuracy Optimization
Implement continual learning loops where ambiguous queries get flagged for human review.
Train models on industry-specific jargon and regional dialects.
Deploy acoustic models that filter background noise in call center environments.

Emotional Intelligence Gap
Integrate sentiment analysis engines that adjust response warmth based on customer mood.
Develop libraries of empathetic response templates for sensitive situations.
Program strategic pauses and conversational pacing that mirror human speech patterns.

Context Preservation Build knowledge graphs that maintain entity relationships throughout conversations.
Implement short-term memory buffers for multi-turn dialog management.
Develop graceful recovery protocols for when misunderstandings occur.

Financial Services Revolution
Modern voice agents now handle complex workflows like:
Detecting potential fraud during calls by analyzing speech patterns for stress indicators. Walking customers through mortgage applications with dynamic form filling. Providing personalized investment advice by integrating with CRM data.

Healthcare Breakthroughs
Pioneering implementations include:
Voice-based symptom checkers that triage patients with 93% accuracy.
Medication adherence systems that adapt reminder frequency based on patient responsiveness.
Mental health screeners that analyze vocal biomarkers for depression risk.

Emerging innovations set to redefine possibilities:
Predictive assistance where AI anticipates customer needs before they articulate them.
Multimodal integration combining voice with AR/VR for immersive support experiences.
Self-improving systems that autonomously refine their knowledge bases from each interaction.

India presents perhaps the most complex linguistic puzzle for AI developers worldwide, with 22 constitutionally recognized official languages, 121 major languages spoken by million+ people each, 19,500+ documented dialects and mother tongues; six distinct language families (Indo-Aryan, Dravidian, Austroasiatic etc.).

This staggering diversity creates unique challenges for Agentic Voice AI systems that must handle:
1. The Multilingual Mindset
Unlike most countries where citizens operate primarily in 1-2 languages, Indians routinely:
Code-switch mid-sentence (e.g. “Yeh document email karo”).
Blend regional language grammar with English vocabulary.
Use hyperlocal expressions that vary by district.

2. The Accent Spectrum A single language like Hindi has dramatic variations:
The clipped consonants of Delhi Hindi.
The lyrical flow of Bhojpuri-infused Hindi.
The Persian-influenced Urdu leanings in Hyderabad.

3. Contextual Nuances Indian communication relies heavily on:
Honorifics that change by region (Ji, Anna, Dada, Bhau).
Culturally specific metaphors (“Make the curry hot” = urgency).
Indirect communication styles for sensitive matter.

To begin this journey, Tunk.ai is laser-focused on the two most widely spoken languages in key Indian markets:
Hindi.
Marathi.

Code-Switch Detection: Identifies when users mix languages.
Emotion Mapping: Recognizes culture-specific vocal cues.
Localization Engine adapts to:
Market-specific measurement units (bigha vs acre).
Regional numbering systems (lakh vs million).
Geographic references (“Near Gandhi statue” vs addresses).

We’re solving for Voice Diversity for:
High-pitched and low-pitched voices in certain regions.
Fast speech patterns (Mumbai vs Chennai pace).
Nasal tonalities in different languages.

Our vision extends to:
Enabling true digital inclusion for non-English speakers.

Creating India’s first emotion-aware Voice AI that understands:
The subtle anger in Punjabi sarcasm.
The layered respect in Tamil formal speech.
The coded humility in Bengali requests.

https://www.linkedin.com/posts/tunkai_voiceai-conversationalai-multilingualai-activity-7306342264933408768-mDQ9?utm_source=share&utm_medium=member_desktop&rcm=ACoAABRfKpoBqoxp4Zt2b9cMKPC5SexTt1fUmjI

During the recent demo, Apurvaa Set, Chief Operating Officer of Tunk.ai, showcased the advanced capabilities of our Agentic Voice AI (AVAI) in a real-world scenario, a food delivery application. The interaction highlighted AVAI’s multilingual adaptability, a critical differentiator in a linguistically diverse market like India.

Key Highlights from the Demo:
Dynamic Language Switching: AVAI initiated the conversation in Hindi, recognizing the user’s context. When Apurvaa responded in English, the system instantly adapted. She then switched between Hindi, Marathi, and English with AVAI accurately processing each transition without latency or errors.
Human-Like Interaction: The AI’s natural, welcoming tone, neutral accent, and smooth delivery closely mimic human conversation, enhancing user engagement and comfort.
Market-Ready Scalability: While this demo focused on a food delivery use case, the underlying technology is designed for cross-industry applications, from customer support to healthcare and banking.

India’s linguistic diversity demands AI solutions that are not just multilingual but context aware and fluid in transitions. AVAI’s ability to process and respond in multiple languages within a single interaction positions it as a gamechanger for businesses targeting pan-India user bases.

Currently supporting key Indian languages, AVAI’s continuous learning framework ensures that as more languages and dialects are integrated, the system will further refine its accuracy and responsiveness.

The rise of Agentic Voice AI marks a paradigm shift in how businesses engage with customers moving beyond transactional interactions to build meaningful, human-like connections at scale. From Diwakar Set’s realization in a boardroom to Tunk.ai’s Bharat-first approach, the journey reflects a deeper truth. Technology must adapt to human complexity, not the other way around.

For India, this means cracking the code of linguistic diversity with AI that understands code switching, regional nuances, and cultural context. For global enterprises, it means deploying systems that don’t just resolve issues but anticipate needs, empathize with emotions, and bridge the gap between efficiency and humanity.

The future belongs to Voice AI agents that don’t mimic humans, but they enhance them. By combining proactive intelligence with emotional resonance, businesses can turn customer service from a cost center into a competitive advantage. The question isn’t whether Agentic Voice AI will redefine industries, it’s how quickly organizations can harness its potential to build trust, loyalty, and seamless experiences in an increasingly digital world.