Open-source RISC-V architecture powers a low-cost alternative to traditional PC chipsets, expanding digital and artificial intelligence access for rural students.
Two semiconductor engineers based in Bengaluru have developed an affordable, artificial intelligence-enabled personal computer named ‘KEO’. Designed to make computing and edge AI capabilities far more accessible, the device relies entirely on open-source RISC-V architecture.
Created as a ‘Made-in-Karnataka’ initiative, KEO provides a low-cost alternative to conventional personal computers powered by proprietary ARM and x86 chip architectures. The creators explained that their primary goal was to construct a processor independent of the heavy licensing fees and royalty models tied to traditional chipmakers.
To handle edge AI processing requirements efficiently, the duo turned to RISC-V—an open-standard instruction set architecture that enables hardware teams to build processors without restrictive vendor licensing.
The project subsequently caught the attention of Karnataka IT Minister Priyank Kharge, who provided input to refine the physical form factor and industrial design.
Beyond its core chip design, KEO relies on open-source solutions across its entire software and hardware stack. The processor is built on RISC-V (pronounced as Risk five) architecture, and operates on a Linux Ubuntu OS.
The computer has undergone rigorous evaluation, successfully passing benchmarks conducted by scientists at the Indian Institute of Science (IISc) and the International Institute of Information Technology (IIIT).
The engineers designed KEO with a clear focus on lowering barriers to computing and AI tools, particularly for pupils in rural and economically disadvantaged areas. Despite recent increases in global RAM prices, manufacturing costs have been successfully kept below $200.
Roll-out in state-run educational institutions is already under way. Over the past year, a non-governmental organization purchased more than 2,000 KEO units for distribution across government schools in Karnataka.
The project highlights how combining open-source hardware with free software can drive down unit costs, democratise edge AI technology, and foster a self-reliant computing ecosystem.
