The Tech Panda takes a look at recent launches in the superfast field of Artificial Intelligence (AI).
Fintech: NPCI announces FiMI, a domain-specific AI language Model built for India’s payments ecosystem
National Payments Corporation of India (NPCI) released FiMI (Finance Model for India), a domain-specific language model built for India’s payments ecosystem, at the India–AI Impact Summit 2026. Developed in-house by NPCI, FiMI currently powers NPCI’s UPI Help Assistant and is designed to address limitations observed in general-purpose large language models when applied to high-scale, high-trust payment workflows.
Vishal Kanvaty, Chief Technology Officer, NPCI said, “FiMI reflects NPCI’s commitment in developing financial language models purpose-built for India’s payments ecosystem. Having successfully built and validated the model, we are now sharing our technical learnings through a detailed paper to contribute to responsible innovation, while strengthening trust, transparency, and collaboration across the ecosystem.”
Features
- Built to natively understand the complexity of Indian payment systems, including UPI, covering transaction dispute handling, mandate lifecycle management, and regulatory and ecosystem queries.
- The model went through continuous pre-training and was further fine-tuned on Indian financial and synthetically generated payments data, enabling accurate reasoning, structured tool invocation, and robust multilingual support.
- The payments-native design allows FiMI to operate reliably in real-world, high-volume transaction environments where accuracy, consistency, and trust are critical.
- Already deployed at a national scale through NPCI’s UPI Help Assistant launched as pilot initiative, an AI-powered conversational support system for UPI users.
- Leverages an agentic AI framework that enables multi-step reasoning to respond to payment related queries, support grievance redressal, and assist with mandate management.
- Currently supports English, Hindi, Telugu, and Bengali, with additional Indian languages planned to be introduced within the next 6 to 8 months to further expand accessibility.
Chatbot: Multilingual Voice AI Platform ‘Ello’ in India
Hyderabad-based digital transformation platform [x]cubeLABS launched Ello, its proprietary multilingual Voice AI platform for Indian enterprises. The platform with voice AI agents adapts across 12 Indian and 100+ global languages and dialects worldwide. This launch positions the company at the forefront of transformative voice-driven digital engagement and strengthens its AI-led growth trajectory.
Sridhar Muppidi, Co-Founder of [x]cubeLABS & Ello, says, “Enterprise AI in regulated industries isn’t just about automation, it’s about reliability, contextual continuity, and measurable outcomes. We have solved some of the hardest problems around long-term memory, context persistence, and production-grade deployment at scale. Many AI systems are built to reduce human call volume. We build systems that actually resolve customer issues end-to-end”.
Features
A self-evolving conversational voice AI platform that adapts across 12 Indian and 100 global languages and dialects worldwide
Chatbot: An Enterprise-Grade Conversational AI Agent for Better Customer Experience
Global enterprise software company Ramco Systems announced its entry into the Agentic AI product segment with the launch of Chia, a conversational AI agent platform designed to redefine how enterprises engage with their customers. Chia is purpose-built for enterprises to reliably automate complex customer support interactions, reducing manual effort, response times, and operating costs, enabling businesses to deliver superior customer experiences at scale.
Abinav Raja, Managing Director, Ramco Systems, said, “Chia addresses a rapidly growing global market need for AI systems that are not just conversational, but truly agentic, capable of reasoning, acting, and delivering measurable outcomes. As our first AI-native product, Chia marks a significant milestone in Ramco’s transformation journey. It is the beginning of a broader roadmap, with many more AI-native innovations planned across our portfolio. This launch is aligned with our vision to transform our entire platform to be AI-native, embedding agentic intelligence into every product we build. We believe the future of enterprise software is agentic by design, autonomous, adaptive, and continuously evolving, and we are committed to leading that transformation.”
Features
- Natural Language Workflow Builder: Design and update AI logics using plain English
- MultiStep Workflow Orchestration: Manage and orchestrate multiple, specialized AI agents for complex, multi-step workflows
- OmniChannel Conversational Presence: Engage users across email, chat, and messaging channels
- RealTime System Integrations: Secure, real-time connectivity with enterprise systems (CRM, ERP, ITSM, HRIS) to execute tasks
- Enterprise Knowledge Search: Deliver accurate, grounded answers from trusted content
- MultiLingual and Multi-Modal: Ability to handle text, and visual inputs across diverse languages, with voice coming soon
- HumanintheLoop Escalation: Seamlessly hand off to support teams with context when needed
- Enterprise?Grade Security and Privacy: Protect sensitive data with role?based access, encryption, audit logs, and built?in compliance controls
- Explainability and Workflow Logs: Gain complete visibility into AI actions, making compliance reporting, auditing, and root-cause analysis effortless
Crypto: GracyAI to Enhance User Interaction Across Its Platform
Bitget, the Universal Exchange (UEX), launched Gracy AI, the first animated digital human in crypto designed to bring real leadership thinking into one-on-one conversations with users. It’s built around the experience and decision-making approach of Bitget CEO Gracy Chen.
“Honestly, I still find it a little funny to see an AI avatar of me on screen,” said Gracy Chen, CEO at Bitget. “But a big part of my job is listening to user concerns, getting close to the details, and helping people understand what’s really happening in the market. The team built Gracy AI around that same approach so more users can connect, learn and grow feeling supported by me and the team,” she added.
Features
- Moves beyond charts and short-term signals. Instead, it gives users a space to talk through market cycles, strategy, career questions, and mindset with an AI that reflects how a real industry leader thinks about growth, risk, and long-term direction.
- Rather than acting as another data layer, Gracy AI focuses on interpretation and context.
- Users can ask about where the industry is heading, how to think through uncertainty, or how to approach decision-making when markets are noisy. The goal is not to predict prices, but to help users think more clearly about them.
Voice AI: CPU Compatible Voice AI Stack for the Next Billion Users
Shunya Labs, a research-driven voice AI company, announced a CPU-compatible voice AI architecture that enables high-accuracy speech recognition and multilingual reasoning on standard commodity servers.
Ritu Mehrotra, Co-Founder and CEO, Shunya Labs commenting on the launch, “Voice is the most natural interface for AI, but it is also the hardest to run reliably at scale. Real-time voice systems require low latency, deterministic performance and strong data sovereignty , all of which break down in GPU-heavy, cloud-dependent architectures. Our CPU-compatible voice stack proves that world-class voice AI can run on the servers organisations already have, making it economically viable, energy-efficient and sovereign by design.”
Features
- Delivers real-time speech recognition and multilingual reasoning on commodity servers , enabling sovereign, low-latency voice intelligence across healthcare, BFSI and government.
- Purpose-built for structured, real-time voice workloads, reducing dependence on GPU clusters and allowing enterprises and public institutions to deploy sovereign, low-latency voice AI directly on their existing infrastructure or devices.
- Enables real-time transcription, multilingual IVR, live agent assist and medical dictation on the x86 servers already used by hospitals, contact centres, government data centres and large enterprises.
