VibeCode30 2026 showcases 30 AI-powered products from India

The Indian government has announced a significant step in the technology sector by introducing three new domestic artificial intelligence models. These models are named EKA-1, Dhir 2B, and Dhir 5B. The Ministry of Information Technology presented these tools as part of the IndiaAI mission, developing them with an emphasis on Indian languages and business processes to reduce dependence on foreign AI models.

These three models were demonstrated during an event held in New Delhi. According to S. Krishna's Secretary of the Ministry of Information Technology and other government officials, these tools can be used in government institutions, research centers, and schools.

A key advantage of two of the three models is their ability to function without an internet connection, allowing them to be used directly on devices.

EKA-1 is the largest of the presented AI tools and was created by the Bangalore-based startup Soket Labs. It is a powerful, open, and hybrid language model designed to solve complex problems. The model is capable of answering difficult questions related to advanced mathematics, software, and logical reasoning, and it can also function as an AI agent to perform multiple operations.

EKA-1 is based on 26.3 billion parameters and was trained on a massive dataset of 7.5 trillion text tokens. This model understands all official Indian languages in addition to English. Thanks to its capabilities, Soket Labs specifically prepared EKA-1 for sectors such as banking financial services and cybersecurity.

The Dhir 2B and Dhir 5B models differ from EKA-1 and were developed to meet various needs. They were created by the company ZenteiQ AiTech Innovation.

The main feature of Dhir 2B and Dhir 5B is that they can operate without internet access. This does not require a large cloud server; they can be downloaded and run directly on a phone or laptop.

India established itself in the 1990s and 2000s as a global back office for software development. At TechSparks 2026, a flagship event by YourStory, one of the founders asked whether the country could achieve similar success in storytelling. He confidently answered yes, as artificial intelligence makes video production more economical and efficient.

A session titled 'Can AI turn India into a global content export hub?' began with a demonstration of Dolphin AI by Saurabh Pandey, founder and CEO of Eloelo Group. This was followed by a discussion in a conversational format with Shraddha Sharma, founder and CEO of YourStory and The Bharat Project.

Pandey noted that India has long produced outstanding intellectual properties such as Baahubali, Kantara, and RRR, but rarely acted as an exporter. He compared this to Japan succeeding with anime, South Korea with dramas, China with microdramas, and the US with Hollywood, emphasizing that each of these countries used content to strengthen its soft power.

In Pandey's view, AI is changing this situation because tools previously available only to a limited number of markets are now open to everyone. Opportunities extend not only to the film industry but also to localized advertising, commercial videos, and social media content intended for international clients.

To illustrate his points, Pandey presented Dolphin AI, Eloelo's newest product. The company initially worked in live entertainment, then moved to microdramas through the Story TV app, and recently added a micro-learning application called Master.

Dolphin AI solves a common problem for content creators: creating a single video often requires stitching clips and edits from about twenty different tools. Dolphin AI replaces this process with an agent chat and a set of templates. A simple prompt allows for the creation of a complete video, while the system independently manages context and narrative continuity. Furthermore, it integrates with Claude and ChatGPT via MCP, helping authors create longer AI-based videos. The presentation concluded with a short demo reel.

When Sharma joined Pandey on stage, she reacted with pride to the demonstration, stating: 'This is amazing. It's real, and it's happening in India.'

The discussion then moved to implementation issues. Pandey reported that during the early access period, Dolphin AI generated approximately 15,000 videos in just eight days solely through organic search.

He then explained why this is important for storytellers. High-quality visual effects previously required huge budgets, which served as a filter determining who could create ambitious stories. Pandey stated: 'With AI, with tools like Dolphin AI, we aim for you to be able to release content without any gatekeepers.' He clarified that AI does not replace actors but replaces expensive locations; for instance, a historical drama no longer needs a real palace. Since distribution has become largely algorithmic, a storyteller from India can reach an audience in the US or Europe.

When asked about the reasons for India's lag, Pandey did not blame creativity. He compared South Korea, with 52 million inhabitants and a content export economy worth about $15 billion, to India's population of 1.4 billion. He countered: 'I would refuse to believe that we lack creativity.' In his opinion, success requires the combination of technology, aspiration, distribution, and capital, and Indian developers too often viewed the domestic market as the only significant one.

Regarding whether microdramas can become a viable business in India, Pandey cited the example of China, where this category brought in about $8 billion in revenue last year and is now growing to $10–11 billion, with one platform earning more than China's entire box office. In India, he said, the aggregate growth rate of the top four or five players exceeds 5,000 crore rupees, achieved in about 18 months.

Historically, high production costs were a barrier, consuming 50–60% of revenue. AI, according to Pandey, finally solves the supply problem. He compared this to the moment of rapid commercialization in the entertainment sector. Pandey expects platforms to consolidate around two or three players, similar to what happened in food delivery and e-commerce, but the supply will remain open. Eloelo released 200 new microdramas last month for its Story TV platform and collaborates with about 90 production companies, a number he predicts will double.

He advised new entrants to focus on the supply side. Small, agile AI studios, consisting of several editors, promo producers, and line producers, can supply microdramas and OTT content to platforms. He urged writers and producers to view AI as a brainstorming partner and proposed the idea of creating an AI-made 'Mahabharata.' Pandey concluded: 'The next Disney or the next major intellectual property can be created right now if the right supply engine appears, because the demand is very obvious.'

Pandey added that Eloelo, which grew from one platform to five, is currently not planning an immediate IPO and is focused on sustainable growth while building the foundation for India's global ambitions.

Sharma noted that Pandey's journey from a Flipkart employee to a globally operating founder serves as a reminder of what Indian ambition can achieve. She urged the audience to tell their teams and networks that the window of opportunity for development in this area is open. The session suggested that if India managed to turn code into global exports, stories could be next.

The co-founder of Murf AI believes that the complexities associated with voice artificial intelligence in India have the potential to shape global technological trends. What Indian users consider ordinary conversation could become the most difficult test for voice AI, and solving this challenge will open up new possibilities worldwide.

Voice AI is capable of answering questions, confirming orders, or assisting with bookings. However, the question arises: can it correctly pronounce an Indian name, understand an address spoken in a mix of Hindi and English, and respond quickly enough to sound natural?

For Sneha Roy, co-founder and COO of Murf AI, such scenarios are not exceptional; they represent the baseline for creating voice AI that will function in India, and ultimately, globally.

During a masterclass at the TechSparks 2026 event titled 'Building Voice AI from India, for India and for the World,' Roy explained how India's linguistic complexity, infrastructure limitations, and economic considerations affect speech technology development.

She cited examples of products that were first adapted for Indian users before finding broader application. Google Maps implemented offline functionality for areas with limited internet access, and Netflix introduced a mobile-only plan that has since been adopted in 78 countries. Uber tested cash payments in Hyderabad before expanding this option to other markets.

Roy posits that voice AI can follow a similar path. For instance, when calling to check a delivery status in Bengaluru, a customer might mix English with a regional language, use a local pronunciation of an address, and expect the postal code to be spoken numerically.

A model built on standardized English may struggle with such nuances. Roy emphasized: 'If a customer has to change their manner of speaking so that the agent can cope, or constantly repeat their address or name, then we have not finished developing it.'

In her view, the task is to create systems that accommodate people's natural way of speaking, rather than requiring customers to adapt to the technology.

Natural speech is only one part of the problem. Voice agents must also react quickly and operate efficiently at scale when companies process millions of calls monthly. Roy reported that a complete voice agent pipeline, including speech recognition, language modeling, and speech generation, typically has a response budget of 500 to 800 milliseconds. She added that Murf has managed to reduce the latency of its text-to-speech model below 100 milliseconds, including network delays.

To achieve this, the company developed Falcon 2—a smaller speech model designed to run on a wider range of GPUs instead of depending on specific, high-performance hardware. Roy noted that this approach helped maintain low latency across different geographical regions while improving cost-effectiveness.

Similar engineering solutions could be beneficial for markets outside India, especially where computational infrastructure is limited or deploying voice agents at scale remains expensive.

Roy also highlighted the importance of a responsible approach to voice data. She mentioned that Murf collaborates with over 400 voice actors globally through long-term, royalty-based partnerships and does not clone voices without consent.

For clients with strict privacy requirements, the company offers APIs that can process data without storing it, as well as on-premise deployments for sensitive applications. Roy's central thesis is that India's linguistic diversity and infrastructural constraints should not be viewed as secondary requirements; they can help define what voice AI must do before it is ready for widespread adoption. As she put it: 'India is the capital of world specifications.'