- Two Indian companies, Arinox AI and KOGO AI, introduced CommandCORE – termed the country’s first sovereign AI product – at the India AI Impact Summit 2026.
- The “AI in a box” system operates entirely on-premise, independent of the internet, aiming to resolve security and privacy risks associated with cloud services.
- According to HiddenLayer’s AI Threat Landscape 2025 analysis, 88% of businesses are concerned about vulnerabilities from integrating third-party AI like OpenAI (ChatGPT), Microsoft Copilot, or Google Gemini.
- A 2025 MIT report shows that 95% of generative AI pilots fail, with privacy being a major factor.
- CommandCORE consists of 4 layers: Nvidia hardware; KOGO’s agentic OS; Enterprise Agent Suite with over 500 connectors; and open-source models for sovereign AI.
- The system runs on Nvidia hardware (Jetson Orin edge, DGX Spark, RTX Pro 6000 Blackwell Server Edition).
- The small version handles models with 1–7 billion parameters; the medium version 20–30 billion parameters; the large version, equivalent to a DGX cluster, can reach up to 405 billion parameters when connecting two machines.
- Starting price is 10 lakh rupees (~$120,000 USD).
- Economic example: An EV charging/battery swap station generates 30TB of data/day; 1,000 stations would generate 30,000TB/day if sent to the cloud.
- The edge solution allows transmitting only about 200GB of filtered data, drastically reducing bandwidth and compute costs.
- Targeting sensitive sectors: finance, banking, government, defense.
📌 Two Indian companies, Arinox AI and KOGO AI, introduced CommandCORE – termed the country’s first sovereign AI product – at the India AI Impact Summit 2026. CommandCORE features offline capabilities, processing from 1 to 405 billion parameters, with prices starting around $120,000. In a context where 88% of businesses worry about third-party AI integration risks and 95% of AI pilot projects fail, an edge model processing 30 TB of data/day on-site and sending only 200 GB to the cloud could create cost and security advantages. This is a move to localize enterprise intelligence rather than relying on global infrastructure.
