How We Transformed Content Management Process for a Leading Pharma Company with AI-Powered Auto-Tagging 

An efficient content management process can make or break a company’s ability to respond to market changes. When a leading pharmaceutical company approached Viseven with challenges in their digital asset management, we saw an opportunity to revolutionize their workflow with AI-powered auto-tagging. This case study explores how our partnership led to remarkable improvements in efficiency, cost savings, and strategic alignment. 

Client Overview 

Our client, a global pharmaceutical leader, was struggling with an ever-increasing volume of content across various engagement channels. Their manual tagging process was holding them back, leading to inconsistencies, errors, and significant time delays in bringing content to market. 

Challenge 

The company faced several critical issues: 

• Low content reuse due to poor searchability 

• Inconsistent and inefficient manual tagging processes 

• Extended project timelines and increased costs 

• Difficulty in measuring campaign effectiveness 

• Challenges in handling specialized medical content 

These problems were not just operational headaches — they were impacting the company’s ability to compete effectively in a rapidly changing market. That is why our client needed a reliable technology partner who could help with the implementation of effective auto-tagging. 

Our Process 

At Viseven, we believe in the power of AI to transform business processes. We proposed an innovative solution: an AI-enabled auto-tagging engine that would connect seamlessly with the client’s digital asset management system (DAM). Our approach involved three key stages: 

1. Training the AI model for strategic tagging: We started by gathering the client’s taxonomy matrix and curated datasets to train our AI model. This ensured the model could accurately assign strategic tags that aligned with the company’s key messages and internal categorization system. 

2. Enabling contextual tagging: We fine-tuned an LLM to generate precise contextual tags, enhancing the descriptive power of the tagging system. 

3. Enriching content assets: Once trained, we connected our AI engine to the client’s DAM system, automatically enriching existing and new content assets with both strategic and contextual tags. 

Throughout the process, we maintained close collaboration with the client, ensuring the solution met their specific needs and aligned with their strategic goals. 

Impact 

The implementation of our AI-powered auto-tagging solution brought about transformative results: 

• Manual tagging work was reduced by 60%, freeing up thousands of human hours for more strategic tasks. 

• The speed of content flow increased dramatically, reducing time-to-market for brand campaigns. 

• With a ROI of over 340%, the solution proved to be not just effective, but highly cost-efficient. 

• Improved tagging accuracy led to better searchability and higher content reuse rates. 

• The solution fostered collaboration across diverse functions, from marketing to IT, driving unified business objectives. 

Our client saw improvements across the board — from content management and workflow optimization to compliance and cost reduction. The AI auto tagging software we implemented became a cornerstone of their digital transformation strategy. 

Ready to Transform Your Content Management Process? 

Whether you’re struggling with content categorization, looking to improve your tagging precision, or aiming to scale your digital asset management, our team of experts is here to help. 

Don’t let manual processes hold your business back. Contact us today to learn how our AI-powered solution can revolutionize your content management strategy. 

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