Brainvire is One Step Ahead in Digital transformation with its new Image Processing System
About
The client is the largest entertainment and news publishing platform. They provide local, national, and international news and other data on their platform. They are renowned in India for ground-breaking digital innovations and support various publishing websites and portals. The company is quite popular, with 150 million page visitors on their site. They wanted to build a new image processing software to provide clients with a safe and engaging user experience across multiple media formats.
Project Highlights
The team wanted a comprehensive multi-media content analysis and profanity detection system to make image processing more versatile. They wanted to combine profanity detection, image intelligence, and content filtering in the new image processing software. The product set a new standard for content moderation, organization, and user satisfaction. It enabled Brainvire to provide its clients with a safer and more engaging user experience across multiple media formats and keep digital transformation one step ahead of the competition.
The Challenges
- Moderating Content in Real-Time:Processing user-generated content in real-time, especially during peak usage, strains the system’s performance.
- Python Versions CompatibilityCompatibility issues due to different Python versions in development and production environments.
- Affected User ExperienceUnexpected errors, exceptions, and edge cases during content analysis and moderation.
- Adapting Content Analysis SystemAdapting content analysis systems is crucial to handle new media formats.
Tech Stack
CSS 3
JavaScript
Python
HTML
MySQL
Azure DevOps
Azure Board
Result
Efficient Content Moderation
A robust integration of a scalable architecture, load-balancing tool, and caching mechanisms allowed the system to maintain responsiveness during high-traffic periods. It ensured efficient content moderation and provided a seamless experience to the users.Improved Consistency Between Different Environments
Clear specifications of different Python version requirements encouraged using virtual environments and setting up testing environments that mirror the production environment’s configuration to catch version-related issues early, reduced version compatibility issues, and improved consistency between development and production.Seamless User Experience
Rigorous testing, implementing robust error handling mechanisms, and integrated detailed logging made it easier to diagnose and troubleshoot issues. It improved system reliability, enhanced user experience, and fastened problem resolution.Adaptability to Changing Media Landscape
Agile development method to maintain a flexible implementation of the extensible models to enable designing collaboration with users to identify emerging media formats and their potential challenges enabled continuous relevancy and adaptability to the changing media landscape, providing content analysis for new formats.
