Semantic tagging has become a cornerstone of modern digital publishing, powering everything from SEO and personalization to internal newsroom workflows. At CUE Days 2025 in Copenhagen, Geneea’s Jirka Hana sat down with Suresh Vijayaraghavan, CTO of The Hindu Group, to discuss how one of India’s most respected news organizations approaches tagging, why they are moving from manual to automated systems, and what this shift means for journalists and readers alike.
In the conversation below, Suresh offers a rare behind-the-scenes look at the scale of The Hindu’s operations and explains why consistent, AI-powered metadata is becoming essential to their future.
Introducing The Hindu and Its Scale of Operations
Jiri: Suresh, thank you so much for joining me today and for taking the time to speak with us. To kick things off, could you briefly introduce yourself and share a bit about The Hindu, the scale of your operations, the size of your newsroom, and so on?
Suresh: Thanks, Jiri, for having me. The Hindu is a 147–148 year old organization. We publish four flagship products: two daily newspapers, The Hindu and Business Line, and two magazines, Frontline and Sportstar. In addition to these, we also produce several supplementary products that accompany the dailies or are distributed independently.
Across The Hindu, we publish 41 print editions and 23 e-paper editions every day. Business Line publishes 16 print editions and six e-paper editions. Altogether, our editorial staff includes more than 750 people, including reporters, desk editors, and senior editors, and we operate more than 30 desks on any given day.
Since moving into digital publishing, our content repository has grown to about 5.2 million published articles. On average, the group produces between 700 and 750 articles a day across the two major dailies and the magazines.
If you look at our total content assets, we have around 54 million text assets in the CUE DAM (a cloud-based digital asset management system developed by Stibo DX specifically for media and publishing companies), covering nearly 148 years of archives, along with about 4 to 4.5 million image assets and almost 10 million PDF files in our archives.
We are headquartered in Chennai in South India, and we are one of India’s major national dailies.
How The Hindu Uses Semantic and Functional Tags Today
Jiri: That is really impressive. Thank you for the overview, it sets the scene perfectly. Now let us talk about semantic tagging, the reason we are here. You have been working with semantic tags, or content tags, for quite some time. Could you walk us through how they are used at The Hindu and what benefits they bring for the newsroom, your readers, or even for the business?
Suresh: Until now, our tagging has been entirely manual. From an article standpoint, we use IPTC tags, and the editorial staff applies them manually.
We also use what we call functional tags. These help us organize and group articles. For example, if we select a tag, we can pull up all articles connected to it and display them together or identify the latest updates on a given topic.
That is one use case, but functional tags mainly drive internal workflows. They mark breaking news, premium versus free articles, or indicate that an article should be included in a newsletter. When an editor feels a piece is suitable for a newsletter, they add the tag and the newsletter system picks it up automatically.
For Business Line, our financial daily, we use tags to identify companies listed on the stock exchange. When an article is written about a listed company, it receives a company tag. This allows us to group all related articles and information about that company at any time.
These tags are used during rendering in the CUE frontend. When a user opens an article about a particular company, the system can immediately display all related content and group the company information in a dedicated section.
Functional tags also help us distinguish magazine articles from daily newspaper content.
So, at a high level, we work with two broad categories of tags: article tags and functional tags. The uses I just described cover the main reasons we rely on them. And for now, everything is still done manually. Our staff applies the tags themselves as they create the articles.
The Move to Automation: Why Shift From Manual Tagging?
Jiri: Looking ahead, you recently completed an upgrade of your CUE platform, congratulations on that.
Suresh: Thank you.
Jiri: And with that upgrade, you also rolled out Geneea’s automated tagging service across your content. Until now, as you said, your journalists have been tagging everything manually. What prompted you to move toward an automated system? Was the goal simply to save time, or are there other benefits you are aiming for?
Suresh: When we evaluated tagging, we looked at five major aspects that convinced us to adopt automated semantic tagging. Saving journalists’ time is certainly a benefit, but the shift is really part of our broader strategy to improve the quality, consistency, and discoverability of our content across all platforms.
The Five Strategic Drivers Behind Automated Tagging
The first aspect is consistency and accuracy. With manual tagging, two people might tag the same article differently, or someone under deadline pressure might forget to add an important tag. Automated tagging ensures that every piece of content is classified using the same taxonomy and logic. That consistency is crucial for downstream uses such as search, personalization, and analytics.
The second aspect is editorial efficiency. We want our journalists to focus on high value work, such as reporting, investigation, and storytelling, rather than repetitive manual tasks. Tagging is a prime candidate for automation.
The third aspect is richer metadata at scale. Automation lets us tag content with far greater depth than humans can reasonably manage. A model can detect entities, themes, sentiment, locations, people, organizations, events, and much more. It can also do this across thousands of articles every day. This creates a detailed content graph that supports both user experience and operational insights.
The next aspect is improving search, recommendations, and SEO. Better metadata leads to better search results and stronger interlinking of articles. When metadata is consistent, external search engines can understand and rank our content more effectively.
Then there is personalization and analytics. Consistent structured metadata is the backbone of personalization. Automated tagging allows us to understand content at a granular level and match it to user preferences. It also helps us analyze coverage trends, engagement patterns, content gaps, and emerging topics.
Finally, we are future proofing our CMS and newsroom workflows. Automated tagging becomes a foundational layer for introducing more AI into the newsroom, such as summarization or language enhancements. It strengthens the entire publishing system.
Looking Ahead: Tagging as the Intelligence Layer of Publishing
To sum it up, automated tagging is not just a workflow upgrade for us. It is a strategic investment in the intelligence layer of our publishing stack. It improves editorial quality, enhances the reader experience, and provides the structured data foundation we need for personalization, analytics, and future initiatives.
Jiri: Thank you, Suresh, for giving us a look behind the scenes at The Hindu and for sharing such a clear picture of what tagging can do for a publishing company like yours.
The Hindu’s move to automated semantic tagging marks a major step toward a more efficient, data-driven newsroom. One where journalists can focus on reporting while AI handles the structural work that powers discovery, personalization, and long-term value.
A big thank-you to Stibo DX for hosting us at CUE Days 2025 in Copenhagen and for the space and support that made this interview possible.
And of course, a big thank-you to Suresh Vijayaraghavan for sharing these insights and for giving us a window into how a leading global publisher is preparing for the next chapter in digital journalism.