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How SunTec Data Boosted AI Accuracy with Scalable Data Annotation Services?

SunTec Data helped a leading predictive audience analytics firm enhance AI model accuracy through large-scale multilingual data and video labeling. The project achieved 99% labeling precision, 65% faster delivery, and improved global audience insight prediction:<br>https://www.suntecdata.com/data-and-video-labeling-services-for-predictive-audience-insights.html

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How SunTec Data Boosted AI Accuracy with Scalable Data Annotation Services?

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  1. How SunTec Data Scaled AI Model Accuracy with 2x Faster Data Annotation?

  2. LEARN HOW SUNTEC DATA IMPROVED AI MODEL ACCURACY FOR A LEADING PREDICTIVE AUDIENCE ANALYTICS FIRM A Case Study on Scalable Data Annotation Services & Video Labeling Services

  3. THE CLIENTS A leading US-based firm specializing in predictive analytics and machine learning. The client utilizes advanced AI tools to predict viewer engagement and provide insights that help optimize targeting strategies, enabling more precise forecasting of shifts in audience preferences.

  4. Key requirements included: PROJECT REQUIREMENTS Labeling and tagging over 2,500 movies, TV shows, trailers, and other content types each month. Providing multilingual support (Spanish and German). Ensuring context-specific and accurate keyword tagging to improve AI predictions of audience engagement. The client required specialized data annotation services to enhance the accuracy of their AI-driven predictive audience engagement model.

  5. PROJECT CHALLENGES Each piece of content required a unique assessment for accurate data tagging, which necessitated significant research. AI reads and interprets written language, identifying key information and sentiment. Maintaining high volume targets (80+ content analyses per day) while ensuring contextual accuracy was crucial. 02. Multilingual annotation for Spanish and German content required native language experts.

  6. OUR SOLUTIONS We assigned a dedicated team of 25 (data labelers + language specialist + QA analyst) responsible for: Content Analysis & Storyline Dissection: We systematically analyzed each piece of content, breaking it down into genres, moods, themes, and character archetypes to ensure accurate tagging. Semantic Keyword Mapping: We tagged both explicit elements (surface- level details) and implied aspects (deeper narrative layers) to capture the full scope of the content.

  7. OUR SOLUTIONS Keyword Ontology Framework: We developed a structured and standardized keyword system that served as a unified dictionary and classification guide, enabling efficient, scalable tagging, ensuring consistency across thousands of assets. Human-in-the-Loop Methodology: We streamlined the labeling process by combining manual validation with automation for scalable solutions wth precision.

  8. PROJECT OUTCOMES Daily Turnaround Time Labeling Accuracy Throughput Reduced to 24-48 hrs (2x faster) Increased to 98-99% (+13-14% increase) Increased to ~100 assets per day (+65% improvement)

  9. READY TO SCALE YOUR AI MODELS WITH ACCURATE LABELED DATA? Connect with us at info@suntecdata.com to learn more about our data annotation services and how we can improve the accuracy and efficiency of your AI model. Read the complete case study here. Website: https://www.suntecdata.com/

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