AI Enrichment
Understand how Lucidya's AI enriches your data : From sentiment analysis and spam detection to Arabic dialect understanding.
8 articles
How Lucidya AI worksAn overview of the AI models and engines powering Lucidya's enrichment capabilities — how data is processed, what intelligence is applied, and how AI-driven insights are generated across the platform.
How Lucidya AI works (FAQs)Common questions about Lucidya's AI infrastructure, model behavior, accuracy, and how AI enrichment applies across different products and data sources.
Sentiment analysis : How to interpret results (Arabic & English)A guide to understanding Lucidya's sentiment analysis output — how positive, neutral, and negative classifications are determined, what influences results, and how to interpret scores in Arabic and English content.
Sentiment analysis : How to interpret results (Arabic & English) - FAQsFrequently asked questions about sentiment scoring, edge cases, language-specific behavior, and how to act on sentiment data in your reports and monitors.
Arabic dialect understanding: What’s supported and how to use itAn overview of Lucidya's Arabic dialect recognition capability — which dialects are supported, how the model identifies them, and how dialect understanding improves analysis accuracy across MENA regions.
Arabic dialect understanding: What’s supported and how to use it (FAQs)Common questions about dialect coverage, model accuracy across regions, and how dialect understanding interacts with sentiment analysis and other AI enrichment features.
Spam detection : What gets filtered and what doesn'tA reference explaining how Lucidya's spam detection model works — what types of content are flagged and filtered, what passes through, and how filtering affects your monitor data.
Spam detection: What gets filtered and what isn’t (FAQs)Frequently asked questions about spam detection behavior, false positives, filter thresholds, and how to manage content that was incorrectly filtered or missed.