Generic models missed brand tone, forcing manual edits. A RAG workflow injecting style guides cut editing effort 30% and boosted quality.
An enterprise platform translates billions of words into more than 450 languages and locales annually for global businesses.
Foundational large language models produced fluent text but lacked the specific tone, terminology, and cultural context required for enterprise...
“Our biggest challenge was striking the right balance between accuracy and fluency. We needed translations that were faithful to our customers’ brand voice while keeping costs manageable.”
AI-powered translation management platform and localization services.
Cloud computing platform and on-demand infrastructure services.
Related implementations across industries and use cases
Manual edits on complex pairs held back delivery. Claude now handles nuance, making 80% of translations publish-ready.
Manual testing couldn't keep pace. Now, AI agents validate code without scripts, cutting test durations by 60%.
Translating the Oxford Dictionary took 39s. A 72-GPU supercomputer cut that to 3.7s, enabling real-time voice translation.
Manual edits on complex pairs held back delivery. Claude now handles nuance, making 80% of translations publish-ready.
Translating the Oxford Dictionary took 39s. A 72-GPU supercomputer cut that to 3.7s, enabling real-time voice translation.
Scattered spreadsheets couldn't catch AI hallucinations. Now, automated LLM judges evaluate every prompt change to block regressions.
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.
Hundreds of pages per board book slowed director prep. Now, isolated AI securely condenses sensitive materials into actionable briefs.
Experts spent 15 minutes pulling data from scattered systems. Natural language prompts now generate detailed reports instantly.
Generic models missed brand tone, forcing manual edits. A RAG workflow injecting style guides cut editing effort 30% and boosted quality.
An enterprise platform translates billions of words into more than 450 languages and locales annually for global businesses.
Foundational large language models produced fluent text but lacked the specific tone, terminology, and cultural context required for enterprise...
“Our biggest challenge was striking the right balance between accuracy and fluency. We needed translations that were faithful to our customers’ brand voice while keeping costs manageable.”
AI-powered translation management platform and localization services.
Cloud computing platform and on-demand infrastructure services.
Related implementations across industries and use cases
Manual edits on complex pairs held back delivery. Claude now handles nuance, making 80% of translations publish-ready.
Manual testing couldn't keep pace. Now, AI agents validate code without scripts, cutting test durations by 60%.
Translating the Oxford Dictionary took 39s. A 72-GPU supercomputer cut that to 3.7s, enabling real-time voice translation.
Manual edits on complex pairs held back delivery. Claude now handles nuance, making 80% of translations publish-ready.
Translating the Oxford Dictionary took 39s. A 72-GPU supercomputer cut that to 3.7s, enabling real-time voice translation.
Scattered spreadsheets couldn't catch AI hallucinations. Now, automated LLM judges evaluate every prompt change to block regressions.
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.
Hundreds of pages per board book slowed director prep. Now, isolated AI securely condenses sensitive materials into actionable briefs.
Experts spent 15 minutes pulling data from scattered systems. Natural language prompts now generate detailed reports instantly.