back_office_ops · media · workflow
Roblox builds a unified multilingual translation model for real-time cross-language chat
Roblox's global platform of more than 70 million daily active users communicating in their native languages across more than 15 million active experiences could not be served by manual translation, and existing AI translation only covered static content rather than real-time chat interactions.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · User sends in-experience chat
A chat message sent within an in-experience text chat session initiates the real-time translation pipeline.
Tools used
LLMML model
Outcome
Roblox deployed real-time AI chat translations across 16 languages with approximately 100ms latency, capable of handling more than 5,000 chats per second, and the model outperforms commercial translation APIs on Roblox content while driving stronger engagement and session quality.
Results
Time savedapproximately 100 milliseconds
Volumemore than 5,000
Grounding & classification
Source type: technical build writeup
26 fields verified against source quotes, 1 dropped as unverifiable.
conversational aiquality inspectiontranslationchat transcripthuman review describedmetric backednamed customerproduction runtime claimedsource backedtools describedworkflow describedmediasoftwareaccuracy improvementcustomer satisfactionthroughput increasetechnical build writeupback office opsautonomous resolution