Delhi-headquartered Netweb Technologies, a two-decade-old “Make-in-India” manufacturer specializing in high-performance servers, storage, and HPC systems, has partnered with Bengaluru-based Bud Ecosystem, the creator of hardware-agnostic generative AI (GenAI) software, optimized small-language-models (SLMs), and an end-to-end AI deployment and management stack. The partnership addresses the challenges of high cost, connectivity issues, and technical talent shortages that have restricted generative AI adoption in India.

Together, they are creating plug-and-play “AI-in-a-Box”—scalable from affordable CPU-only boxes for kirana stores, village schools, SMEs, and remote farmers, up to advanced GPU, HPU, and NPU clusters suitable for research institutes, universities, and large enterprises. These pre-configured appliances integrate Bud’s efficient multilingual SLMs, inference optimization engine, and domain-specific agents (such as teaching assistants, farmer support, customer support, and retail operations), along with built-in security and governance guardrails. Use cases range widely, including offline education assistants, personalized retail management for kiranas, healthcare and agricultural advisory agents for rural regions, and internal AI copilots for enterprises. Engineered specifically to meet India’s infrastructural and linguistic diversity, the solution ensures affordability, data privacy, low operational overhead, and scalability, serving as a practical template for AI adoption in other developing nations facing similar constraints.

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Who are Netweb and Bud?

Netweb Technologies brings over two decades of expertise as a premier Original Equipment Manufacturer (OEM) for servers, storage, backup, and high-performance computing (HPC) systems. The company has consistently supported India’s digital transformation with locally manufactured and serviced computing solutions. Bud Ecosystem, based in Bengaluru, develops innovative generative AI (GenAI) software, providing universal runtime environments and state-of-the-art Small Language Models (SLMs) optimized for Indian languages. Bud’s software stack is uniquely hardware-agnostic, running efficiently on CPUs, GPUs, HPUs, NPUs, and TPUs.

Addressing India’s AI Accessibility Challenges

Currently, generative AI solutions remain predominantly accessible only to large enterprises due to high infrastructure costs, complexity of GPU deployments, expensive cloud-based services, and the technical expertise required to manage such systems. Small businesses, educational institutions, healthcare centers, and rural communities in India face significant barriers—high operational expenses, poor internet connectivity, data privacy concerns, and talent shortages—that exclude them from harnessing the transformative potential of AI.

Swastik Chakraborty VP Technology, from Netweb Technologies said, “Our collaboration
with Bud Ecosystem reinforces our vision of building trusted, scalable, and inclusive compute
infrastructure for India’s digital growth. Together, we are making AI accessible where it
matters most; across communities, institutions, and enterprises.”

Netweb and Bud Ecosystem have partnered to create specialized “AI-in-a-Box” systems, engineered from hardware through to AI software, agents, and models. These systems deliver outcome-focused AI with defined Service Level Objectives (SLOs) optimized for affordability, reliability, performance, and ease-of-use, directly addressing India’s unique infrastructure and operational constraints.

Customers can begin with a simple Intel Xeon CPU-based appliance and seamlessly scale up to GPUs, HPUs, or NPUs from vendors such as AMD, Nvidia, or Intel, without the prohibitive capital expenditures typically associated with data center remodeling. Bud ensures continuous, automatic model updates and optimizations, eliminating the complexity of maintenance and ensuring consistent, state-of-the-art accuracy.

Linson Joseph, Chief Strategy Officer (CSO) from Bud Ecosystem added, “This partnership
brings together Bud Ecosystem’s deep expertise in AI software with Netweb’s proven
strengths in hardware and middleware engineering. Our shared mission is to make advanced
AI truly deployable—anywhere and everywhere—from metropolitan hubs to the most remote
corners of rural India. Together, we aim to simplify and localise AI for every sector that stands
to benefit from it.“

What the Combined Product Offers

The partnership will offer plug-and-play edge AI systems known as “AI-in-a-Box,” packaged with optimized hardware from Netweb and Bud’s AI software stack, including multilingual AI models like HEX1, efficient inference engines, and specialized AI agents for various domains. The product tiers include:

• Starter Tier: CPU-only appliance for basic AI tasks.
• Growth Tier: Mixed CPU and commodity GPU appliances for SMEs.
• Pro Tier: High-end GPU/HPU/NPU systems for enterprises and research institutes.

All appliances are designed for immediate deployment with minimal setup, operating offline without internet dependency, ensuring complete data sovereignty and security. These optimized AI systems can empower diverse sectors:

• Education: Remote schools can deploy teaching assistants delivering localized language support without the internet.
• Healthcare: Rural clinics gain AI-driven diagnostic and patient management tools that keep sensitive patient data secure.
• Agriculture: Farmers access multilingual crop advisory and weather prediction without high-bandwidth internet.
• Retail: Kirana stores leverage real-time sales analytics and personalized inventory recommendations.
• SMEs: Small businesses implement customer support agents and business automation tools at minimal operational costs.
• Enterprises and Research Institutions: High-performance setups enable internal copilots, research assistants, document management agents, and advanced GenAI applications.

Built for India, A Blueprint for the Global South

The Netweb-Bud solution addresses critical infrastructural and linguistic realities of India, such as intermittent power supplies, varied internet connectivity, and linguistic diversity. With built-in native-language models (Hindi, Kannada, Telugu, Tamil, Malayalam), low-power operation, and affordable pricing structures, the solution is perfectly tailored to India’s diverse conditions. This model also offers a replicable template for AI democratization in other developing countries facing similar infrastructure and economic constraints.