2024 marks a transformative phase for AI in India, with groundbreaking advancements in AI models that integrate local languages, cultural nuances, and practical applications. Supported by government initiatives aimed at fostering homegrown AI startups, these developments have not only empowered Indian businesses but also established benchmarks for the global AI ecosystem. 

This article highlights the best Indian AI models of 2024, showcasing their pivotal role in advancing AI innovation and strengthening India's position as a leader in the global AI landscape.

​BharatGen

India's recent strides in AI are exemplified by the launch of BharatGen, a government-funded initiative focused on developing multimodal Large Language Models (LLMs) tailored to India's specific needs. This initiative underscores the nation's commitment to AI innovation and its potential to drive economic growth.

A significant milestone within this initiative is unveiling e-vikrAI, an advanced Vision Language Model solution designed to revolutionize the Indian e-commerce landscape. By automating the cataloguing process through image-based input, e-vikrAI significantly reduces sellers' manual effort. This innovative solution leverages deep cultural understanding to generate accurate and relevant product information, including titles, descriptions, features, and pricing suggestions.

Sarvam-1

Sarvam AI, a prominent Indian AI startup, has made significant strides in natural language processing (NLP) with the launch of Sarvam-1. This innovative large language model (LLM) is optimised explicitly for Indian languages, addressing a critical gap in the AI landscape.

Sarvam-1, boasting 2 billion parameters, supports ten major Indian languages, demonstrating its potential to revolutionize various applications such as language translation, text summarization, and content generation. A key differentiator of Sarvam-1 lies in its computational efficiency. It offers significantly faster inference speeds than larger models while maintaining competitive performance levels, making it well-suited for deployment in resource-constrained environments, including edge devices.

NVIDIA Nemotron-4-Mini-Hindi-4B

NVIDIA CEO Jensen Huang's recent visit to India witnessed the launch of Nemotron-4-Mini-Hindi-4B, a compact yet powerful Hindi language model designed to empower businesses to create AI solutions tailored to regional demands. This model, part of NVIDIA's NIM microservice, is optimized for deployment on NVIDIA GPU-accelerated systems, ensuring efficient performance across diverse applications.

Tech Mahindra has become an early adopter of this technology, integrating it into its Indus 2.0 platform and focusing on Hindi and its dialects. Nemotron Hindi model's hybrid training approach yields top-notch AI performance across various benchmarks. Its microservice architecture facilitates seamless integration into diverse industry applications, including education and healthcare.

Chitralekha

Chitralekha is an open-source video transcreation platform developed by AI4Bhārat, a leading AI research organization. Leveraging advanced AI models, Chitralekha empowers users to generate and edit audio transcripts in various Indic languages effortlessly. Its core functionalities include subtitle generation, audio/video dubbing, and video translation across multiple languages, making it a valuable tool for content localization and accessibility. The platform's open-source nature encourages community contributions and fosters innovation in AI-powered video processing.

Everest 1.0

SML’s Hanooman has unveiled Everest 1.0, a versatile multilingual AI system designed to cater to various Indian languages, including Hindi, Bengali, Tamil, and Telugu. The system currently supports 35 languages and is poised to expand its language capabilities to 90 shortly. Powered by the innovative Executable Expert Model (EEM) architecture, Everest 1.0 excels in real-time data access, predictive analytics, and image analysis tasks.

By leveraging AI, Everest 1.0 aims to enhance accessibility and inclusivity in critical sectors like customer service, education, healthcare, and finance.

Surya OCR

Surya OCR is a cutting-edge optical character recognition (OCR) toolkit designed to process a wide range of document types and languages accurately. Developed by Vik Paruchuri, the recently released v2 significantly enhances accuracy across all document types, surpassing Tesseract and Google Cloud OCR.

Surya OCR excels in detecting and analyzing various document layout elements, including tables, images, headers, and more. Its seamless integration with Python 3.9+ and PyTorch simplifies installation and usage. Users can leverage its powerful command-line interface or API for diverse OCR tasks, from basic text extraction to complex layout analysis.

Surya OCR offers a flexible and efficient solution that empowers users to automate document processing workflows and extract valuable information from various sources.

Disclaimer:

We have not tested the AI models mentioned in the article. For any clarifications or further information, please consult the respective development team.