Soket Labs and ZenteiQ unveil indigenous AI models under IndiaAI Mission

Soket Labs and ZenteiQ Advance India's AI Capabilities

Soket Labs and ZenteiQ AiTech Innovations unveiled new indigenous AI models under the IndiaAI Mission at a launch event in New Delhi attended by MeitY Secretary S Krishnan1

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. The homegrown foundational AI technologies include Soket's EKA-1 and ZenteiQ's Dhir 2B and Dhir 5B models, marking a significant step in building India's domestic AI ecosystem. Both Indian startups were selected under the mission's IndiaAI Innovation Centre pillar to develop indigenous foundation models with subsidized AI compute and research support2

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EKA-1 Targets Complex AI Applications

Soket's 26.3 billion parameter EKA-1 model was trained on nearly 7.5 trillion tokens and supports all 22 scheduled Indian languages as well as English2

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. Described as an open, sparse hybrid language model, EKA-1 is designed for mathematics, code generation, reasoning and agentic applications. Soket Labs cofounder and CEO Abhishek Upperwal explained that the model addresses India's unique banking, financial services and cybersecurity landscape, delivering solutions aligned with the country's needs and priorities2

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ZenteiQ's Multilingual Models Enable On-Device Deployment

ZenteiQ introduced Dhir 2B and Dhir 5B as open-source multilingual models supporting English and 10 other Indian languages2

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. These models focus on smaller multilingual assistants that operate in environments with limited connectivity. ZenteiQ CEO Sashikumar highlighted that the models offer flexibility to run across different computing platforms, including GPUs and TPUs, with their lightweight architecture enabling on-device deployment on mobile phones without cloud connectivity2

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. This approach enhances privacy, security and accessibility by allowing users to access AI capabilities locally while keeping data on their devices. The models support on-premise deployment and applications such as document-grounded automation, knowledge retrieval and use cases across government and education sectors2

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Strategic Push for Technological Autonomy

MeitY Secretary S Krishnan emphasized that indigenous AI models will strengthen India's technological autonomy while improving productivity across government, industry and research2

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. The IndiaAI Mission represents the government's commitment to building a robust domestic AI ecosystem and reducing dependence on foreign AI technologies1

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. This initiative positions India to compete globally while addressing local requirements and cultural nuances through models trained on Indian languages and use cases.

Broader AI Innovation Landscape

Separately, Sarvam AI announced the launch of Prism, an open-weight decision model built on its Sarvam 105B model2

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. Prism targets enterprise workflows such as customer-support routing, security checks and evaluation of AI-agent activity, reporting an average score of 71.8 across three evaluation indices and a median response time of 44 milliseconds on an NVIDIA B200 GPU. The Indian enterprise AI ecosystem is projected to become a $71 billion market opportunity by 2030, driving continued innovation from homegrown AI startups2

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. Watch for benchmark results, deployment details and pricing information as these indigenous foundation models move toward commercial availability.