Integrated Stable Video Diffusion with open-source LLaMA model to generate training videos from text descriptions for corporate learning platforms, reducing content creation costs by 70%.
A Fortune 500 company needed to scale their corporate training program across 50,000+ employees but faced significant challenges with traditional video production. Creating high-quality training content was expensive, time-consuming, and required extensive coordination between subject matter experts, video production teams, and learning designers.
Key challenges included:
We developed an innovative text-to-video generation platform that combines the narrative capabilities of open-source LLaMA with the visual generation power of Stable Video Diffusion, creating a comprehensive solution for automated training video production.
Open-source LLM for script generation and narrative structuring
State-of-the-art video generation from text prompts
AI-powered voice synthesis and narration
Video processing and post-production automation
LLM workflow orchestration and prompt management
Model hosting and inference infrastructure
LLaMA analyzes training requirements and generates structured video scripts
AI breaks down script into visual scenes with detailed descriptions
Stable Video Diffusion creates video segments from scene descriptions
Whisper generates natural-sounding narration from the script
Automated editing, transitions, and quality enhancement
Our solution's breakthrough lies in the seamless integration of multiple AI models working in harmony:
Reduced training video production costs by 70%, from $10,000+ per video to under $3,000, while maintaining professional quality standards.
Accelerated video creation by 10x, reducing production time from 4-6 weeks to 2-3 days for complete training modules.
Generated over 1,000 training videos in the first year, covering 200+ topics across 15 languages and multiple business units.
Achieved 92% average quality rating from learners and 89% completion rates, exceeding traditional video training performance.
Successfully deployed and optimized open-source models in enterprise environment:
Language Models: LLaMA 2, LangChain, Hugging Face Transformers
Video Generation: Stable Video Diffusion, FFmpeg, OpenCV
Audio Processing: Whisper, TTS models, audio enhancement
Infrastructure: NVIDIA A100 GPUs, Kubernetes, Docker
Development: Python, PyTorch, FastAPI, Redis
This implementation represents a breakthrough in automated content creation, demonstrating how open-source AI models can be successfully integrated into enterprise workflows. The solution has established new benchmarks for cost-effective, scalable training content production.
The project showcases HertzDB Labs' expertise in combining multiple AI technologies to solve complex business challenges while leveraging open-source solutions for maximum flexibility and cost efficiency.