Accessing AI Data — AIKosh Portal, India’s National AI Data & Model Repository Under The IndiaAI Mission (2025)

Policy Update
Prisha Sachdeva

Background 

IndiaAI Mission was launched in March 2024 and is centered on addressing existing gaps in data, research, and skill mismatch so that the benefits of AI can contribute to the growth of our country. The Ministry of Electronics and Information Technology (MeitY) identified seven pillars: IndiaAI Compute, Foundation Models, AIKosh, IndiaAI Application Development Initiative, FutureSkills, Startup Financing, and Safe & Trusted AI.

The goal of this mission is AI for All, with an outlay of ₹10,371 crore over five years to build a comprehensive AI ecosystem in the country. AI is worth $120 billion as a market, is growing by more than 20% each year, and is expected to reach a total of $1.5 trillion by 2030. Further, the global market for AI-specialized hardware is expected to grow 9x to $90 billion by 2030.

The AIKosh pillar was officially launched on 6 March 2025 by Union Minister Ashwini Vaishnaw under the Ministry of Electronics and Information Technology (MeitY), with the aim to democratize access to AI-ready resources.

These strategies are designed to address key structural challenges in India’s AI ecosystem.

Functioning

AIKosh, India’s AI and dataset platform, is a government-operated hub of datasets, models, and development tools under the Ministry of Electronics and Information Technology (MeitY), serving as a core pillar of the IndiaAI Mission.

Before AIKosh, datasets in India were fragmented across ministries, universities, hospitals, and private organizations. Engineers had to spend a lot of time collecting, cleaning, and validating data to develop AI models. The cost of accessing private data was also too high, and without a license, the data could not be verified.

To address these challenges, IndiaAI envisioned a single platform comprising datasets from government and private institutions. The goal of AIKosh is to make data affordable, authentic, and compliant with privacy regulations, while also providing built-in AI tools for experimentation and model training.

 These efforts aim to eliminate fragmented and siloed datasets, the high cost of AI computing infrastructure (GPUs), the Western or global bias embedded in existing AI models trained on non-Indian data, and the privacy risks associated with using untrusted or randomly sourced data.

Institutional framework

The AIKosh platform was built under the IndiaAI Mission by the Ministry of Electronics and Information Technology (MeitY) in collaboration with the National e-Governance Division (NeGD) and Daffodil Software, which developed the platform.(https://aikosh.indiaai.gov.in/home)

How it operates

AIKosh is a government-operated hub that hosts datasets, models, and tools in a categorized format, allowing students, researchers, and developers to access or download available resources. 

Individuals can browse and download data, but only institutions or contributors can provide datasets to the platform. Students across disciplines can also access datasets, models, hackathons, and workshops. 

Access levels

The platform uses three access levels: open, restricted, and private. At the open level, any individual can access the data. At the restricted level, any individual can view the data, but the contributor’s approval is required to download it. At the private level, only the contributor can grant access to the data.

 Purpose

The downloaded data can be used by students, researchers, and developers for projects, research, developing sovereign foundational models, creating India-specific AI models, and participating in hackathons and competitions. 

Funding structure 

The IndiaAI Mission was implemented with a total outlay of Rs. 10,371.92 Cr for a period of 5 years. The detailed budget for 7 pillars is as follows 

Source: Ministry of Electronics and Information Technology, Lok Sabha reply (2026). 

Performance

So far, the performance of AIKosh has been incredibly impressive. The platform has adopted a number of datasets and models since launch. 

Source – IndiaAI — AIKosh Platform Launch (PIB, March 2025)

IndiaAI — AIKosh Platform Hub

PIB Fact Sheet — IndiaAI Mission Progress (December 2025)

The table shows strong growth in AIKosh, with the highest expansion seen in datasets and models. 

Impact

The impact of the AIKosh pillar under the IndiaAI Mission is highly promising, as its vision of eliminating fragmented data, Western bias, and barriers to affordable access to data appears to be being achieved. This scale of growth indicates that AIKosh has moved beyond a pilot-stage repository to becoming a genuinely active national resource — one that institutions are willing to contribute to and that a growing base of users are actively drawing from, rather than a platform with data sitting unused.

Contributions from diverse institutions such as IIT Bombay, Sarvam AI, and government ministries show that organizations are putting in significant effort to build the platform and make it useful.

The data is also being used to build AI models, as startups are using the available data to develop AI models suited to Indian culture. For instance, Sarvam AI has drawn on AIKosh’s repository to train large language models tailored to Indian languages, while BharatGen has used platform datasets to build multilingual foundation models — demonstrating that AIKosh’s data is directly feeding into India’s sovereign AI development, rather than remaining unused

The platform also promotes inclusivity, as students, researchers, and institutions can access the data.

Since launch, the numbers have been high and suggest strong adoption, though whether this translates into meaningful downstream outcomes remains to be seen.

Emerging issues

While the AIKosh platform has scaled rapidly, these rates raise concerns that could affect its long-term credibility.

Since its launch, we have seen high growth; however, the Ministry did not set a target to be achieved, so it is difficult to estimate whether the platform has actually been useful. The number of datasets, models, and downloads available on the platform has increased by 46x, 4.1x, and 2.1x, respectively, but there is no data showing the usefulness of this content or whether it was actually helpful in building projects or developing solutions.

The platform is inclusive in terms of accessing data, with some restrictions, but it is exclusive in terms of uploading datasets, as this is restricted to institutions only. This leaves out freelancers, data scientists, and others. The high growth rate also raises concerns about the quality and verification of the data.

Way Forward

The next and foremost step for the AIKosh platform should be to declare target numbers so that progress can be tracked transparently, and to establish criteria that allow individual professionals to contribute as well, thereby increasing inclusivity.

The next phase should be to introduce a quality-check platform, staffed by a team of specialized individuals to verify the data. It should also explicitly mention all projects made using that data so that it can be used by the general public.

With clearer targets, broader contributor access, and stronger quality assurance, AIKosh has the potential to move from being a fast-growing repository to a genuinely foundational infrastructure for India’s sovereign AI ambitions.

References

IndiaAI. (2026). AIKosh — Datasets. https://aikosh.indiaai.gov.in/home

IndiaAI. (2026). AIKosh platform hub. https://indiaai.gov.in/hub/aikosh-platform

Ministry of Electronics and Information Technology. (2025, March 6). India’s AI revolution: A roadmap to Viksit Bharat [Press release]. Press Information Bureau. https://www.pib.gov.in/PressReleasePage.aspx?PRID=2108810&reg=3&lang=1

Ministry of Electronics and Information Technology. (2025, March 6). MeitY launches AIKosha, a secured platform that provides a repository of datasets, models and use cases to enable AI innovation [Press release]. Press Information Bureau. https://www.pib.gov.in/PressReleasePage.aspx?PRID=2108961&reg=3&lang=1

Ministry of Electronics and Information Technology. (2025, May 30). India’s common compute capacity crosses 34,000 GPUs [Press release]. Press Information Bureau. https://www.pib.gov.in/PressReleasePage.aspx?PRID=2132817&reg=3&lang=1

Ministry of Electronics and Information Technology. (2025, December 30). Transforming India with AI: Over ₹10,300 crore investment & 38,000 GPUs powering inclusive innovation [Fact sheet]. Press Information Bureau. https://static.pib.gov.in/WriteReadData/specificdocs/documents/2025/dec/doc20251230747901.pdf

Ministry of Electronics and Information Technology. (2026). Lok Sabha unstarred question no. 3246: IndiaAI Mission budget and labs data. Government of India. https://sansad.in/getFile/annex/270/AU3246_wa5YLu.pdf?source=pqars

About the Contributor

Prisha Sachdeva is a Research & Editorial intern at IMPRI. She’s pursuing a Bachelor’s in Psychology (Honours) from the University of Delhi. Her interest lies in cognitive science and human behavior, with a focus on evidence-based policy and behavioral research.

Acknowledgment

The author extends sincere gratitude to the IMPRI team for their invaluable guidance throughout the process.

Reviewed by: Kavin Adithya

Publisher: Pallavi Lad

Disclaimer: All views expressed in the article belong solely to the author and do not necessarily represent the views or policies of the organisation.

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