Devnagri is Building a Multilingual ‘Brain’ to Enable Companies Expand to Tier 2 &amp; 3 Cities
Hyperlocal content is becoming crucial for businesses to expand into tier two and tier three cities in India. Devnagri, a data-driven generative AI company, is paving the way by developing a solution, which they call the brain for Indian companies. Nakul Kundra, the co-founder and CEO, told AIM about the moat of the company in the era of Indic AI startups. “Devnagri is dedicated to helping businesses move into new markets by providing hyperlocal content. Our machine translation capabilities enable businesses to transform their digital content into multiple languages, allowing them to engage with diverse customer bases,” Kundra explained. Based in Noida and founded in 2021, Devnagri specialises in personalising business communication for non-English speakers. The company had recently raised an undisclosed amount in a Pre-Series A round led by Inflection Point Ventures. These newly acquired funds will be used for marketing, sales, technology enhancement, R&D, infrastructure, and administrative expenses. Devnagri leverages open-source LLMs, such as the latest Llama 3, integrating it with its existing dataset and proprietary translation engine for 22 languages. It tailors business communications for diverse linguistic audiences, seamlessly integrating its technology into both private and government infrastructures. “We built application layers on top of our machine translation engine,” Kundra elaborated. “These layers allow customers to upload documents, select languages, and even customise the content before translation. The system understands specific tones and terminologies, ensuring that the translated content aligns with the business’ communication style.”Similarly, New York-based RPA firm UiPath recently partnered with Bhashini. The focus of this collaboration is the integration of Bhashini’s language models with the UiPath Business Automation Platform. This will facilitate seamless translations of documents and other essential areas, specifically targeting Indian languages supported by Bhashini. Companies such as CoRover.ai and Sarvam AI are also in the similar field of building translation capabilities for companies. Even big-tech companies, such as Microsoft and Google, are heavily focused on translation into Indic languages for catering to the Indian market. What’s the Moat Then? However, Kundra said that Devnagri’s proprietary technology lies at the heart of this initiative, and also the moat of the company. “We’ve created our own machine translation capabilities from scratch,” Kundra said. “Businesses can use our APIs to integrate this technology directly into their platforms, localising content in real-time.” Devnagri’s dataset is robust, comprising over 750 million data points across 22 Indian languages. “We initially built our models using a vast dataset, and recently we’ve incorporated SLMs and LLMs to enhance quality and address grey areas identified through customer feedback,” Kundra said. The goal is to create a single brain for businesses, integrating all touchpoints and datasets into a cohesive system that understands and responds in the desired tone. “We adapt existing models and integrate them with our proprietary technology, ensuring high-quality multilingual capabilities,” Kundra added. Collecting data for such a comprehensive system is no small feat. “Our data comes from multiple sources, including open-source dataset corpus, customer data, and synthetic datasets we create,” Kundra explained, saying that the introduction of new datasets from Bhashini also helps the company improve its models. Devnagri’s multilingual capabilities extend beyond text-to-voice-based conversational bots. “We are developing multilingual bots that allow customers to interact in their preferred languages, whether it’s Marathi, Kannada, or any other language,” Kundra said and added that they aim to reduce the latency to as little as possible. The Road Ahead When asked about Devnagri’s differentiating factor, Kundra emphasised on their multilingual bots. “These bots are essential for companies operating pan-India. They handle calls in multiple languages, switching seamlessly to accommodate the caller’s preference, all with the lowest latency.” Security and privacy are paramount, especially when dealing with government organisations, and customers such as UNDP, and Apollo, among several others. “All our modules are proprietary, enabling us to bundle and position them securely within enterprises or government agencies,” Kundra assured. Devnagri’s journey has been remarkable, marked by notable milestones like their appearance on Shark Tank India 2022. “Multilingual conversation is the need of the hour, and our solutions aim to optimise costs and improve efficiency for enterprises.” The firm has also received numerous prestigious awards, including the TieCon Award 2024 in San Francisco, the Graham Bell Award 2023, and recognition as NASSCOM’s Emerging NLP Startup of India. “Our machine translation engine is a foundational model. It enables us to build conversational bots that understand and respond in multiple languages, tailored to specific business needs,” Kundra said. As Devnagri looks to the future, their focus remains on building comprehensive AI solutions that cater to the diverse linguistic landscape of India. “We aim to create an ecosystem where businesses can thrive in any language, offering seamless multilingual interactions and superior customer experiences,” Kundra concluded.
Devnagri’s dataset is robust, comprising over 750 million data points across 22 Indian languages.
Based in Noida and founded in 2011, Devnagri specialises in personalising business communication for non-English speakers.
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Mohit writes about AI in simple, explainable, and often funny words. He's especially passionate about chatting with those building AI for Bharat, with the occasional detour into AGI.