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An international pharmaceutical company needed to scalably create professional video materials for medical staff. The focus was on accuracy of terminology, stable quality of output, and an efficient process from recording to publishing on a closed portal for HCPs.
We were faced with typical post-production challenges: poor audio quality, manual editing of deaf spots, time-consuming transcripts and subtitling, the need for consistent audio and video quality, and the requirement for fast delivery. The client expected a solution that would reduce production time without compromising professional accuracy and that could be easily extended to other therapeutic areas.
The main objectives were:
1. Manual work
Manual editing and subtitling took too much time, which slowed down the delivery of finished videos.
2. AI and security
Conventional AI models failed to capture the technical terminology correctly, leading to frequent corrections.
3. Quality
Consistent audio and video quality across the series of videos was not ensured.
We deployed local AI models adapted to medical terminology, which formed the core of the new production pipeline:
Automated editing: the model identified and removed dead sections and pauses, reducing manual interventions in the timeline.
Accurate transcription and subtitling: the domain-specific model for specialized terminology generated subtitle evidence significantly more accurately than generic solutions, so corrections were short and targeted.
Quality control: each video was manually verified by a medical staff member who fine-tuned terminological nuances and ensured compliance with internal standards.
Sound and image: We applied AI audio enhancement and consistent color grading to make the series look uniform and professional.
Publishing: We uploaded the finished materials in a structured way to a new closed medical portal for healthcare professionals.
Future support: we have prepared a plan to actively support the portal with targeted ads and social networks.
In total, we edited more than 25 hours of material
Time saved thanks to AI
Compared to the original plan, we managed to reduce the lead time by 3 months
Dozens of doctors in more than 10 locations
