Complex localization tasks required constant human oversight. Now, collaborating AI agents automate entire workflows like subtitling and translation.
A cloud-based media services provider that manages over 14 million media assets for global broadcasters, studios, and streaming platforms like Disney Star and CBS.
The company sought to automate complex, long-duration media localization tasks like subtitling, language translation, and transcript generation....
“Since the launch of CLEAR, we’ve seen media operations evolve from manual to software-driven asset management, but AI is taking that to a new level—automating human-in-the-loop workflows entirely for greater efficiency.”
Media ERP software and cloud content operations for the entertainment industry.
Cloud computing platform and on-demand infrastructure services.
Prime Focus Technologies's Content localization is part of this use case:
Related implementations across industries and use cases
Translating updates one language at a time bottlenecked distribution. Now, AI drafts multilingual commentary in minutes for editor review.
Model tuning took weeks, slowing market entry. On Bedrock, updates take days, cutting costs 50% and boosting retention 75% for telecom.
Legacy migrations took 12.5 man-months. Engineers now set the architecture and let AI handle bulk coding, freeing them to focus on QA.
Translating updates one language at a time bottlenecked distribution. Now, AI drafts multilingual commentary in minutes for editor review.
Model tuning took weeks, slowing market entry. On Bedrock, updates take days, cutting costs 50% and boosting retention 75% for telecom.
Manually illustrating vintage assets would have tripled production time. Now, a 3-person team uses AI to generate and animate the visuals.
Custom analytics required months of full-stack development. Now, self-serve AI apps connect analysts directly to data models.
On-premise systems, dispersed and brittle, bottlenecked every release. AI agents now run routine dev steps — hours cut to minutes.
A mistranslated word could derail global R&D projects. Now, researchers instantly refine technical papers & communicate seamlessly across languages.
Complex localization tasks required constant human oversight. Now, collaborating AI agents automate entire workflows like subtitling and translation.
A cloud-based media services provider that manages over 14 million media assets for global broadcasters, studios, and streaming platforms like Disney Star and CBS.
The company sought to automate complex, long-duration media localization tasks like subtitling, language translation, and transcript generation....
“Since the launch of CLEAR, we’ve seen media operations evolve from manual to software-driven asset management, but AI is taking that to a new level—automating human-in-the-loop workflows entirely for greater efficiency.”
Media ERP software and cloud content operations for the entertainment industry.
Cloud computing platform and on-demand infrastructure services.
Prime Focus Technologies's Content localization is part of this use case:
Related implementations across industries and use cases
Translating updates one language at a time bottlenecked distribution. Now, AI drafts multilingual commentary in minutes for editor review.
Model tuning took weeks, slowing market entry. On Bedrock, updates take days, cutting costs 50% and boosting retention 75% for telecom.
Legacy migrations took 12.5 man-months. Engineers now set the architecture and let AI handle bulk coding, freeing them to focus on QA.
Translating updates one language at a time bottlenecked distribution. Now, AI drafts multilingual commentary in minutes for editor review.
Model tuning took weeks, slowing market entry. On Bedrock, updates take days, cutting costs 50% and boosting retention 75% for telecom.
Manually illustrating vintage assets would have tripled production time. Now, a 3-person team uses AI to generate and animate the visuals.
Custom analytics required months of full-stack development. Now, self-serve AI apps connect analysts directly to data models.
On-premise systems, dispersed and brittle, bottlenecked every release. AI agents now run routine dev steps — hours cut to minutes.
A mistranslated word could derail global R&D projects. Now, researchers instantly refine technical papers & communicate seamlessly across languages.