Intelligent annotation for content moderation, online safety, platform integrity, and responsible AI systems
High-fidelity annotation for text, images, videos, audio, and multimodal content across digital platforms. Eidoryx supports AI systems that need to identify harmful, inappropriate, abusive, deceptive, or policy-violating content while maintaining consistent and context-aware moderation standards.
10 annotation types for content moderation & trust & safety data.
Annotating harmful, abusive, threatening, hateful, discriminatory, spam, or policy-violating text. These datasets support automated moderation, platform safety, conversational AI, and safer online communities.
Identifying and classifying potentially harmful, inappropriate, violent, graphic, or policy-violating visual content. These annotations support computer-vision moderation systems and large-scale content screening.
Labeling hateful, discriminatory, harassing, insulting, or targeted content based on project-defined policies and taxonomies. These datasets support safer social platforms, community management, and AI-powered moderation.
Identifying violence, weapons-related imagery, injuries, graphic scenes, threats, and other project-defined categories of harmful visual content. These datasets support automated safety detection and content-risk classification.
Classifying content according to project-defined adult, suggestive, or sexually explicit categories. These datasets support age-appropriate content filtering, platform safety, and automated moderation systems.
Identifying project-defined self-harm, suicide-related, dangerous-behavior, or harmful-instruction content. These datasets support safety classification, risk detection, and responsible AI systems.
Annotating spam, phishing attempts, fraudulent content, misleading promotions, impersonation, and other project-defined deceptive behaviors. These datasets support platform integrity, fraud prevention, and automated content filtering.
Labeling project-defined misinformation, misleading claims, manipulated content, and contextual indicators. These datasets support content-integrity systems, information-quality analysis, and AI-assisted moderation.
Analyzing combinations of text, images, video, audio, captions, comments, and metadata to understand content within its broader context. These datasets support multimodal moderation and advanced AI safety systems.
Evaluating AI-generated content for safety, policy compliance, harmful outputs, factuality, bias, and other project-defined risk categories. These datasets support AI evaluation, model safety, red-teaming, and responsible AI development.
Built for complex content moderation and trust & safety environments, where harmful, deceptive, or policy-violating content must be identified accurately and consistently across multiple data formats. Eidoryx combines structured annotation with policy-driven, context-aware quality workflows to create reliable datasets for content moderation, platform safety, AI safety, spam detection, harmful-content detection, misinformation analysis, multimodal moderation, LLM evaluation, responsible AI, and digital trust systems.
Talk to our team about annotation programs, datasets, and enterprise AI infrastructure tailored to your domain.
