# From Zero to Hero: Localization-Led Generative AI at Udemy

DevFeed: [From Zero to Hero: Localization-Led Generative AI at Udemy](<https://devfeed.tech/articles/from-zero-to-hero-localization-led-generative-ai-at-udemy-26355.md>)

Original publisher: [Read original article](<https://medium.com/udemy-engineering/from-zero-to-hero-localization-led-generative-ai-at-udemy-a422e4f968d4?source=rss----19c6d3367ed4---4>)

Author: Nishanth Gandhidoss

Published: 2025-09-22T17:47:18Z

Content type: article

Language: en

Sources: [Udemy Engineering](<https://devfeed.tech/sources/udemy-engineering.md>)

Topics: [Localization (l10n)](<https://devfeed.tech/topics/localization.md>), [Generative AI](<https://devfeed.tech/topics/generative-ai.md>), [Large Language Model](<https://devfeed.tech/topics/llm.md>), [datasets](<https://devfeed.tech/topics/datasets.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [features](<https://devfeed.tech/tags/features.md>), [generative-ai](<https://devfeed.tech/tags/generative-ai.md>), [generative-ai-tools](<https://devfeed.tech/tags/generative-ai-tools.md>), [implementation](<https://devfeed.tech/tags/implementation.md>), [llm](<https://devfeed.tech/tags/llm.md>), [llm-applications](<https://devfeed.tech/tags/llm-applications.md>), [machine-learning](<https://devfeed.tech/tags/machine-learning.md>), [machine-translation](<https://devfeed.tech/tags/machine-translation.md>), [retrieval-augmented-gen](<https://devfeed.tech/tags/retrieval-augmented-gen.md>), [techniques](<https://devfeed.tech/tags/techniques.md>), [translation](<https://devfeed.tech/tags/translation.md>)

## AI overview

Udemy describes how it localized generative AI features, including Skills Mapping and its in-course AI Assistant, to serve learners in multiple languages. The article compares translation management systems, multilingual LLMs, and hybrid strategies, emphasizing trade-offs among implementation speed, language coverage, fluency, cultural nuance, and domain precision.

## Source excerpt

By Nishanth Gandhidoss, Senior Staff Data Scientist @ Udemy Why Multilingual Generative AI Matters Generative AI is rapidly changing how people learn and work, but those gains are only realized when the technology speaks the user's language. Over the past year at Udemy, we prioritized breaking the English-only barrier so our Gen AI features, most critically Skills Mapping and the in-course AI Assistant, could deliver value for learners across the globe. Our approach balanced speed, coverage, and quality, allowing us to move quickly without sacrificing fidelity in markets where nuance matters. Below we describe the localization strategy we adopted, why we made those trade-offs, and the operational practices that made the rollout repeatable, scalable, and quick. Localization Strategies When deciding how to localize a Gen AI product, it is helpful to think of options on a spectrum from low to high complexity. The simplest approach provides broad language coverage fast, while the most involved approach optimizes for fluency, cultural nuance, and domain precision. At Udemy, we researched and organized our work around three primary strategies: a translation management system (TMS) for rapid implementation with broader coverage, a multilingual LLM system (MLS) for high-fidelity experiences, and a hybrid approach to balance reach and quality. As each strategy is introduced below, we briefly explain the industry-standard localization techniques they draw on, with examples, so the differences are clear. Translation Management System (TMS) At the simplest end of the spectrum, we have the TMS approach. With a TMS, the user interacts in their own language, but the AI model itself operates in English input/output. The system first detects the user's input language, say, in Spanish, and sends the input through a machine translation (MT) service that converts it into English. The LLM then generates an English response, and that response is translated back into the user's input lang