Success Story: Content moderation with AI for retail and social platforms

In an increasingly globalized, hyper-connected and exposed digital ecosystem, the visual and textual content that a brand or community publishes not only represents its identity, but can also trigger significant consequences in terms of public perception, cultural sensitivity and even legal repercussions. What an organization communicates – intentionally or not – can influence its reputation, credibility and relationship with its audiences. Therefore, identifying and filtering offensive, inappropriate or potentially sensitive content at an early stage has become a strategic necessity, both for companies and for social or non-profit organizations.

Aware of this reality, at hiberus we have developed a content moderation system based on artificial intelligence, capable of proactively protecting business and third sector organizations from the risks derived from digital exposure. 

What we did

We have designed and deployed a multimodal moderation platform, capable of automated analysis of both images and text before they are published. Thanks to its approach based on advanced artificial intelligence models, the system can detect problematic content with a high level of accuracy, operating in real time or through batch processing.

Notable detection capabilities include:

• Presence of weapons, violent symbolism or explicitly aggressive images.
• Religious representations or sensitive cultural elements out of context.
• Hate speech, xenophobic messages or incitement to violence.
• Discriminatory language based on gender, race, sexual orientation, religion or origin.
• Content that is sexualized, inappropriate or violates ethical codes.

In addition, the solution is highly flexible and can be integrated into multiple digital channels, including e-commerce platforms, community forums, social networks, chatbots, suggestion boxes, review systems and more.

Use cases

We have already successfully applied this technology in different sectors, demonstrating its scalability and effectiveness:

🛍️ International retail: we perform automated analysis of more than 30,000 images every week in digital catalogs, marketplaces and advertising campaigns, with the aim of avoiding the publication of offensive, misinterpretable or culturally inappropriate elements.

🌍 NGOs and social platforms: we help moderate user-generated content (UGC) in open digital communities, ensuring that virtual spaces are respectful, inclusive and safe for all participants.

These cases demonstrate that, beyond the industry, there is a growing demand for technology solutions that prevent reputational crises and foster healthy digital environments.

How it works

Our solution combines different artificial intelligence technologies, computer vision, natural language processing (NLP) and cloud services. The system is composed of the following key components:

• BLIP: language-vision model that generates automatic image descriptions and answers questions about visual content.

• YOLO: neural network specialized in object detection and localization, used to identify offensive or dangerous elements.

• MobileNet: lightweight architecture optimized to recognize complex cultural patterns such as traditional textiles, religious iconography or local symbology.

• LLaMa 3.2 Instruct: PLN model oriented to classify texts with high sensitivity to hate speech, harassment, stigmatization or misinformation.

• Claude Sonnet: multimodal model with high accuracy in moderating mixed content (image + text), useful for analyzing integrated publications.

• External APIs: such as Azure Content Moderator and Google Cloud Vision, integrated as additional reinforcement.

• Data sources: we use public datasets (Roboflow, Kaggle), web scraping (Wikimedia, Unsplash) and synthetic image generation with Stable Diffusion under commercial license.

Results achieved

The system has proven its effectiveness and value in real environments:

✅ Automated detection of 31 categories of offensive symbols and inappropriate elements.
⚙️ Batch processing of thousands of images in seconds, enabling frictionless scaling of content review.
🔍 Significantly improved reputational protection as well as digital environment safety for brands and communities.

Why it matters

A misinterpreted image or a misplaced message can trigger an immediate reputational crisis, generate viral reactions, cause cancellations, boycotts or even legal sanctions. In the case of NGOs or social platforms, the risks are even more sensitive, as they can affect the trust, emotional security and well-being of users.

Our solution allows you to act in advance, minimizing risks and aligning the content published with the values, norms and ethical standards of each organization. It is a system that not only filters out problematic content, but also allows you to communicate with greater responsibility, sensitivity and cultural coherence.

At hiberus, we firmly believe that technology should be at the service of respect, inclusion and integrity. With this content moderation platform, we demonstrate that it is possible to scale digital processes without losing the human context, helping brands and communities to protect their image, build safer environments and strengthen the trust of their audiences.

We have an expert team in Generative AI and Data that have developed GenIA Ecosystem, an ecosystem of proprietary AI solutions to meet any challenge. Tell us about your project!