Two dynamic companies, Yu and Neysa, have raised substantial funds to expand in instant food production and AI-driven cloud solutions.
Yu, an instant food and beverage brand, raised INR 55 crore (about $6.6 million) in a Series B funding round led by Ashish Kacholia and the Asian Paints Promoter Group. The funds will be used to expand distribution channels and strengthen Yu's 100% fruit juice product line.
Founded in 2021 by Bharat Bhalla and Varun Kapur, Yu offers a wide range of healthy, all-natural packaged foods. Initially focused on instant cup noodles and pasta, the brand has now added ready-to-cook noodles and natural beverages. Yu's unique products, like 100% Whole Wheat Noodles and 100% Coconut Water, have quickly become popular.
Yu’s products are available in over 7,500 stores across India and are listed on major quick-commerce platforms like Blinkit and Swiggy. The company recently expanded to South Africa with 2,000 retail outlets and is experiencing rapid growth. Its founders plan to triple revenues over the next two years through new launches and broader distribution.
Neysa, an AI and cloud infrastructure startup, raised $30 million in an all-equity Series A round co-led by NTTVC, Z47 (formerly Matrix Partners India), and Nexus Venture Partners. The funding will expand Neysa’s AI infrastructure and R&D capabilities, laying the foundation for its AI acceleration cloud services.
Founded by Sharad Sanghi and Anindya Das in 2023, Neysa provides AI and machine learning infrastructure as a service. Its flagship platform, Velocis, launched in July, offers on-demand cloud services with a focus on private and public cloud flexibility. Neysa serves research institutes, AI startups, and enterprise clients in sectors like banking and manufacturing. With 12 active clients, Neysa is planning to go global with its next funding round.
Neysa also differentiates itself by providing open-source solutions with no client lock-in, allowing for flexible customization. The company’s infrastructure consulting helps customers optimize their AI requirements cost-effectively.