How AdTech Uses AI and MLtwist to Apply Brand Safety Classifications

Introduction

In digital advertising, ensuring brand safety is critical to maintaining consumer trust and protecting brand reputation. The industry has established guidelines to help advertisers standardize brand safety and suitability measures.

This adtech company developed a product that employs a combination of natural language processing (NLP) and computer vision (CV) to analyze digital content at a granular level. This allows the system to assess the suitability of text, images, video, and audio in real time. However, ensuring high-quality training data for AI models remains a challenge. This is where MLtwist plays a key role in optimizing their data preparation process.

THE CHALLENGE

Enhancing Brand Safety with IAB Compliance

1. Improving Quality and Accuracy

MLtwist provides its client with high-quality, structured datasets that they use to assess their model performance. By automating and refining data labeling processes, MLtwist enhances the precision of its customer’s contextual analysis, reducing false positives and negatives in brand safety assessments. This means that ads are less likely to be mistakenly flagged as unsafe, while true risks are identified more effectively.

2. Reducing Cost and Increasing Efficiency

Manual data labeling and annotation are time-consuming and expensive. MLtwist’s automated data preparation significantly reduces these costs by streamlining the ingestion, cleaning, and structuring of unstructured data from various sources. By reducing the reliance on costly manual reviews, this adtech company achieves faster turnaround times while maintaining high levels of accuracy in brand safety classifications.

Results and Industry Recognition

• Higher Accuracy: The adtech’s AI models now deliver more precise contextual brand safety recommendations, reducing errors by a significant margin.
• Cost Savings: By reducing manual annotation and increasing automation, they have cut down data processing costs while improving operational efficiency.
• Scalability: MLtwist enables faster AI model updates, allowing its client to keep pace with evolving digital content trends and IAB standards.

Conclusion

By integrating MLtwist into its AI-driven workflow, this adtech company has strengthened its ability to apply IAB guidelines accurately and efficiently. MLtwist’s data preparation capabilities have helped improve brand safety recommendations while reducing operational costs, making it a game-changer in the adtech and digital advertising space.