AI-Powered Automated Subject-Wise Video Generation

Problem

This project focused on automating the creation of videos for multiple subjects by reading the structured document content with an AI-based video generation platform (Pictory AI).

Automating the creation of videos for multiple subjects using the Pictory AI platform.
Dynamically reading and processing multiple .doc files organized in subject-wise folder structures.
Handling secure, session-based login authentication to the platform without interrupting automation flow.
Mapping document content to subject-specific video creation workflows.

Solution

A scalable automation framework was developed using Java, Selenium WebDriver, and Java native I/O libraries.

Document Ingestion Layer
- Implemented Java NIO (Files.walk, Path, DirectoryStream) for recursive folder traversal.
- Used FileInputStream and buffered readers, Java native methods to extract document content.
Authentication and Session Management
- Selenium WebDriver was configured to handle dynamic login workflows.
- Persistent browser sessions were maintained to avoid repeated authentication failures.
AI Platform Automation Layer
- Navigate to content creation modules within the Pictory AI interface.
- Programmatically populate text areas with subject-wise document content.
- Trigger video generation workflows for multiple subjects.

Results

Significantly reduced manual effort in video creation.
Improved speed and consistency of video production.
Enabled scalable video generation for multiple subjects.
Reduced the risk of human errors caused by repeated manual tasks.

Business Impact (Before and After)

Metrics	Before Automation	After Automation
Video Creation Time	Several hours per subject, fully manual	Automated generation in around 5 minutes per subject
Document Processing	Manual extraction from DOC files; repetitive and error-prone	Automated ingestion of multiple DOC files using Java NIO
Consistency of Video Content	Inconsistent formatting and variations between subjects	Standardized, uniform video creation across all subjects
Scalability	Difficult to scale; linear increase in manual workload	Highly scalable; multiple subjects processed without additional effort
Human Errors	High risk due to repetitive copying and manual data entry	Errors minimized due to end-to-end automation
AI Workflow Integration	Not integrated; relied on manual navigation of Pictory AI	Automated workflows fully integrated with the AI platform
Operational Efficiency	Low efficiency due to manual steps	High efficiency with continuous, unattended automation

Development Timeline

The end-to-end automation framework was designed and developed within 2–3 days, covering document ingestion, seamless authentication handling, and AI-driven video generation workflows. The solution efficiently processed over 48 subjects, in which a few subjects contained multiple modules, where automation took around 5 minutes per video and the entire video creation was completed within a week, instead of several weeks of manual effort.

This rapid and large-scale delivery demonstrates Sarvika’s capability to:

Integrate quickly with third-party AI platforms
Automate complex, multi-step UI workflows
Transform time-intensive manual operations into a scalable, repeatable automation pipeline

Conclusion

The automated video creation framework delivered a repeatable, scalable, and error-free process for generating subject-wise videos using Pictory AI. It showcases Sarvika’s expertise in building high-impact automation solutions that seamlessly integrate with modern AI platforms.