Back office ops · Production

Projector Institute localizes Russian lectures into Ukrainian with Pitch Avatar AI voice cloning, saving up to 90% of dubbing time

The problem

Projector Institute had hundreds of hours of educational content recorded in Russian before 2022, and after deciding to discontinue Russian-language content, faced the challenge of localizing lectures while preserving the natural tone and character of lecturers' voices — re-recording was infeasible because many content creators could not produce high-quality re-recordings and the process would have required extensive team resources.

Workflow diagram · grounded in source
1
Pilot localization initiated
trigger
“we initiated a pilot project to localize the content while maintaining its original quality”
2
AI translation
ai_action
“Authentic translation with AI”
3
Voice cloning
ai_action
“Voice cloning for realistic delivery”
4
Lip-sync synchronization
ai_action
“Synchronizing the translated content with the lecturers' lip movements and lecture dynamics using AI, delivering a seamless and natural experience”
5
Localized lecture published
output
“Lectures are now available in Ukrainian, broadening accessibility for the audience”
Reported outcome

Lectures are now available in Ukrainian, preserving 100% authenticity of lecturers' voices, and the localization process saved up to 90% of time and resources in dubbing.
The audience praised the new format and Projector Institute met growing demand for Ukrainian educational content without utilizing internal team resources.

Reported metrics
Dubbing time and resources savedup to 90%
Authenticity of lecturers' voices preserved100% authenticity
Reported stack
Pitch Avatar
Source
https://pitchavatar.com/case-studies/how-projector-creative-and-tech-online-institute-localized-training-materials/
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

Lectures are now available in Ukrainian, preserving 100% authenticity of lecturers' voices, and the localization process saved up to 90% of time and resources in dubbing.

What tools did this team use?

Pitch Avatar.

What results were reported?

Dubbing time and resources saved: up to 90%; Authenticity of lecturers' voices preserved: 100% authenticity (source-reported, not independently verified).

How is this back office ops AI workflow structured?

Pilot localization initiated → AI translation → Voice cloning → Lip-sync synchronization → Localized lecture published.