Aivar partnered with the client as its dedicated AI-Studio, rebuilding its conversational AI from the ground up—replacing the reactive chatbot with a multi-agent orchestration layer capable of reasoning, acting, andpersonalizing at scale.

Multiple specialized AI agents, each purpose-built for a distinct function, work in concert to handle complex,multi-step lending support scenarios. A contextual cross-selling engine proactively surfaces relevant productrecommendations based on each customer's journey and behavior, turning support interactions into revenuegenerating touchpoints. Real-time voice support brings the platform's capabilities to voice-first users for the firsttime, and expanded multilingual coverage now serves a significantly broader slice of India's lending market.The entire solution is built on cloud-native infrastructure, ensuring effortless scalability and compliance with nore-indexing required when new products are added.

The platform is designed as a production-grade, cloud-native multi-agent system:

• Multi-Agent Orchestration: Specialized agents covering data retrieval, business rule enforcement,response generation, document workflows, and smart escalation—coordinated under a unified agenticreasoning layer.
• Real-Time Voice Layer: Low-latency voice interaction support enabling natural spoken conversationsacross the platform's customer base for the first time.
• Multilingual Engine: Full conversational support across Hindi, English, and Tamil, enabling consistentCX across regional demographics.
• Contextual Cross-Sell Engine: Behavior- and journey-aware recommendation logic embedded withinconversation flows, surfacing relevant financial products at the right moment.
• Dynamic Knowledge Management: Content updates applied in real time without full re-indexing,eliminating bottlenecks that previously slowed product and policy rollouts.
• Smart Escalation: Confidence- and complexity-based routing ensures human agents handle onlygenuinely complex cases, maximizing automation coverage.

• 15–20% Cross-Sell Conversion Uplift: The contextual cross-selling engine drives measurable revenuelift by surfacing the right product recommendations within live support conversations.
• Sub-3-Second Response Latency: End-to-end responses across chat and voice are delivered in under 3seconds, enabling a seamless, real-time customer experience.
• Multilingual Coverage Expanded to 3+ Languages: Support now spans Hindi, English, and Tamil,unlocking a broader and more diverse customer base across India.
• 40–50% Reduction in Agent Repetitive Workload: Human agents have recovered nearly half theirbandwidth, now focused on complex, high-value interactions.
• Zero Re-Indexing for New Product Lines: New products and content updates are onboarded withoutinfrastructure overhauls, dramatically accelerating time-to-market.
• 30–40% Reduction in Support Operating Costs: Automation and intelligent self-service have deliveredsignificant, sustained savings across the support function.