Building AI with MongoDB: How Devnagri Brings the Internet to 1.3 Billion People with Machine Translations

Devnagri, an Indian AI-powered translation platform, was founded by Himanshu Sharma to bridge the language gap for India's 1.3 billion non-English speakers, enabling access to the internet in their native languages. The platform uses a custom transformer model based on the MarianNMT neural machine translation framework and is built on MongoDB Atlas, providing API access and a plug-and-play solution for dynamically translating applications and websites. The company has partnered with Google Vertex AI and Tensor Processing Units (TPUs) to host its models, and is now evaluating off-the-shelf models such as OpenAI GPT-4 and the Llama-2-7b foundation models. MongoDB's flexibility and performance make it an ideal fit for Devnagri's machine translation needs, allowing for scalable distributed architecture and parallelization of read and write requests across multiple nodes in the cloud.

Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.