Fake News Detection | Social Media Platforms
Application of the Fake News Detection Model for Social Media Platforms (With Voice Differentiation) Use Case: Real-Time Identification and Blocking of Fake News Posted by Users or Content Groups Market: Social media platforms such as Facebook, Twitter, TikTok, etc. In the current social media ecosystem, where posts and user-generated content can […]
Read MoreFake News Detection | Non-Governmental Organizations (NGOs)
Application of the Fake News Detection Model for Non-Governmental Organizations (NGOs) Use Case: Detection of Misinformation Related to Social Impact Issues such as Climate Change, Human Rights, or Public Health Market: NGOs, international organizations, and development agencies. In critical issues such as climate change, human rights, and public health, misinformation can […]
Read MoreFake News Detection | Public Relations and Marketing Companies
Application of the Fake News Detection Model for Public Relations and Marketing Companies (With Voice Differentiation) Use Case: Reputation Monitoring and Detection of Fake News that May Affect a Company or Public Figure’s Image Market: Public relations, marketing, and reputation management companies. In an environment where fake news can severely affect […]
Read MoreFake News Detection | Governments and Public Organizations
Application of the Fake News Detection Model for Governments and Public Organizations (With Multimodal Processing and Voice Differentiation) Use Case: Monitoring Disinformation Campaigns That May Interfere with Elections, Public Health Crises, or Major Events Market: Communication ministries, electoral bodies, cybersecurity agencies. In critical moments such as elections, public health crises, or natural disasters, disinformation […]
Read MoreFake News Detection | Cybersecurity Companies
Application of the Fake News Detection Model for Cybersecurity Companies (With Multimodal Processing and Voice Differentiation) Use Case: Detection of Fake News in Phishing Campaigns or Disinformation Cyberattacks Market: Cybersecurity companies, monitoring platforms, and defense against cyberattacks. In today’s digital environment, phishing attacks and disinformation campaigns have become a constant threat […]
Read MoreFake News Detection | Education and E-Learning Platforms
Application of the Fake News Detection Model for Education and E-Learning Platforms Use Case: Validation of Educational Content and Detection of Misinformation on Online Learning Platforms Market: Universities, e-learning platforms, educational centers In the education and e-learning sector, the accuracy and quality of educational content are crucial to ensure that students […]
Read MoreChatbot Detector | Patients During Remote Consultations
Emotion and Intention Detection of Patients During Remote Consultations Using the API REST /virtualbot/sentiment/sentiment_analisys Market: Clinics, hospitals, telemedicine platforms. Description: The API REST /virtualbot/sentiment/sentiment_analisys, which utilizes advanced OCR and a multimodal LLM, enables real-time analysis of patients’ emotions and intentions during remote consultations through telemedicine. This analysis provides healthcare professionals with […]
Read MoreChatbot Detector | Related to Claims and Policies
Evaluation of Emotions and Intentions in Interactions Related to Claims and Policies Using the API REST /virtualbot/sentiment/sentiment_analisys Market: Insurance companies, claims adjusters. Description: The API REST /virtualbot/sentiment/sentiment_analisys, using advanced OCR and a multimodal LLM, allows real-time analysis of customers’ emotions and intentions during their interactions with insurance companies. The emotional analysis […]
Read MoreChatbot Detector | Customer-Financial Advisor Interactions
Emotion and Intention Analysis in Customer-Financial Advisor Interactions Using the REST API /virtualbot/sentiment/sentiment_analisys Market: Banks, insurance companies, fintechs. Description: The REST API /virtualbot/sentiment/sentiment_analisys, utilizing advanced OCR and a multimodal LLM, enables real-time analysis of customers’ emotions and intentions during their interactions with financial advisors. This analysis detects emotions such as frustration, confusion, […]
Read MoreChatbot Detector | Customer Service Interactions
Evaluation of Customer Service Interactions Using the REST API /virtualbot/sentiment/sentiment_analysis Market: Companies with high volumes of customer interactions (banks, telecommunications, utilities). Description: The REST API /virtualbot/sentiment/sentiment_analysis, which utilizes advanced OCR and a multimodal LLM, allows real-time analysis of customer service interactions. Sentiment analysis can detect frustration, confusion, or satisfaction, while intent […]
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