Jun 13, 2025

Copied As businesses across India accelerate the adoption of GenAI, the demand is shifting from scripted chatbots to intelligent, autonomous agents capable of delivering outcomes. Gupshup is leading this evolution by deploying domain-specific AI Agents that are locally contextual, compliant by design, and ready to scale across Tier 2–3 markets. In this exclusive conversation, Krishna Tammana, CTO, Gupshup, shares how Gupshup is advancing India’s AI journey — from no-code platforms for regulated industries to language-first innovations for a multilingual population. At the helm of Gupshup’s technology and engineering strategy, Krishna is focused on building AI systems that are secure, scalable, and human-centric, particularly for high-stakes sectors like BFSI and healthcare. With over 20 years of leadership experience at global tech firms including Talend, Splunk, E*TRADE, and Sybase, he brings deep expertise in cloud infrastructure, data architecture, and SaaS transformation. Q With AI adoption booming across APAC and India amid rising concerns around trust, security, and job displacement, how is Gupshup enabling innovation while addressing these critical consumer anxieties in sensitive sectors like BFSI and healthcare? A AI adoption promises major efficiency gains but also raises critical challenges, especially in sensitive sectors like BFSI and healthcare. Concerns around data privacy, regulatory compliance, transparent AI decision-making, and workforce impact can slow down enterprise AI integration. To address this, organizations need AI systems that are secure, explainable, and trustworthy by design. That’s where Gupshup comes in. We address these by embedding strong guardrails and compliance protocols within our AI Agents. Our recently launched Agent Library offers specialized, pre-trained AI models designed for specific business functions such as customer onboarding and claims processing. These agents provide reliable, context-aware responses while maintaining strict control over tone, accuracy, and data privacy, ensuring alignment with regulatory standards. For instance, Tonik Bank uses Gupshup’s ACE LLM-powered AI agents to automate 75 percent of customer queries, enabling a 4.3 times boost in team productivity and projected savings of over $20 million in three years. In healthcare, AI adoption faces similar challenges including the need for high accuracy in patient interactions, and the importance of maintaining empathy and trust. AI solutions can support healthcare providers by automating appointment scheduling, patient follow-ups, and administrative tasks, thereby improving efficiency while ensuring compliance and patient confidentiality. Q As the industry shifts from reactive chatbots to autonomous agentic AI, how is Gupshup evolving its platform to lead this transition and differentiate itself in a crowded conversational AI market? A The conversational AI landscape is shifting from reactive chatbots to autonomous agents that manage complex workflows, personalize interactions, and deliver complete customer journeys. Businesses are recognizing the need to evolve with this shift and embrace digital assistants that drive real outcomes. In response, Gupshup has enhanced its platform and introduced its AI Agent Library. These pre-built, domain-specific agents are optimized for use cases across industries such as banking, insurance, retail, and utilities. Each agent comes configured with enterprise-grade features like tone control, fallback protocols, data privacy safeguards, and real-time system integrations. Unlike traditional scripted chatbots, Gupshup’s agents are trained to manage structured tasks such as lead generation, appointment booking, support requests, and onboarding. The platform includes tools for deployment, monitoring, analytics, and continuous improvement. Enterprises can configure these agents without writing code, using a no-code interface that aligns with security and compliance standards. To accelerate adoption, Gupshup allows businesses to “rent” AI agents instead of building from scratch. This model supports faster go-to-market and reduces dependency on engineering resources. Its platform also supports multilingual and multimodal channels including messaging apps and voice, enabling broader reach and consistent customer experiences. Q How is Gupshup’s no-code platform balancing enterprise-grade customization and compliance to empower regulated industries like finance and healthcare to deploy precise, brand-aligned AI agents without deep developer involvement? A In regulated industries like finance and healthcare, AI adoption is growing, but so are the barriers. Strict compliance requirements, the need for customization, and limited developer resources can slow deployment. Enterprises need ways to move fast without compromising control, safety, or brand alignment. Gupshup’s no-code platform addresses this with pre-built AI Agents tailored to specific business use cases. These agents integrate securely with enterprise systems to enable real-time, compliant interactions. Enterprises can quickly deploy AI-driven workflows for customer support, onboarding, and lead generation, without building from scratch. The platform also includes tools for ongoing monitoring, analysis, and refinement. Customers can choose which parts of a flow AI should handle using configurable hooks in the no-code interface. Gupshup also offers out-of-the-box agentic AI packages. Deployment involves connecting data sources, configuring behavior, and light tuning, which Gupshup handles. Each month, tuning becomes easier as more out-of-the-box agents require minimal adjustments. Increasingly, businesses in sectors like real estate, retail, and finance prefer renting these AI agents. This enables faster, scalable, and compliant adoption all without the burden of building and maintaining complex infrastructure. Q Drawing from your experience at Talend and Splunk, what are the key infrastructure and integration challenges you've faced at Gupshup, and what are your top technology priorities heading into 2025? A In the context of AI, our workloads for most part are very manageable. The key aspect of making this work is to deliver quality at the right performance. Out of the box, LLMs are slow when you choose high quality and can hallucinate if you choose performance. What we do to achieve both is to take smaller models that are fast but fine tune them for our use cases and industries to ensure high quality. Fine tuning does require infrastructure that is expensive and can take some time to run. This too is getting faster and cheaper by the day. Q As Indian enterprises adopt GenAI-powered CX for multilingual and Tier 2–3 markets, how is Gupshup optimizing its tools and architecture to scale across local infrastructure gaps and cultural complexities? A Serving India’s Tier 2 and 3 markets with GenAI customer experiences requires more than translation. It demands contextual, culturally aware, multilingual AI that scales across local infrastructure challenges. Enterprises need conversational platforms that balance personalization with performance in mobile-first, low-bandwidth environments. Gupshup is one of the few companies providing the necessary infrastructure, architecture, and AI capabilities. Our platform supports local languages and popular messaging channels like WhatsApp and RCS, enabling authentic regional engagement. We also integrate voice AI, allowing natural speech interactions in preferred languages, essential in markets with lower literacy or limited text use. We support multiple languages for GenAI-powered CX through our own ACE LLM. This LLM can be configured, trained, and deployed anywhere, supporting many languages. Our brands have served Tier 1, 2, and 3 markets and continue to do so thanks to this language support and regional deployment flexibility. Our AI Agents are personalized and integrate with enterprise systems to handle diverse intents efficiently, even under infrastructure constraints. This enables enterprises across retail, BFSI, and government to deliver GenAI-powered experiences that truly resonate, unlocking deeper engagement and trust.