AI Enrichment
Unlock smarter workflows, faster access, and full control of content with AI-powered enrichment, tagging, searches, summaries, and translations.
From Raw Articles to Smart Content
X-CAGO’s AI-powered technology augments newspapers and magazines into fully optimized, structured content. Using Entity Recognition with WikiData and IPTC Mediatopics Tagging, each article is enriched and exported in XML or JSON for seamless multi-channel use. Advanced AI search with a RAG chatbot ensures reliable answers with full source transparency, while automated summarization and translation make content instantly more accessible and shareable.
Enriching Content with AI
X-CAGO’s AI technology enhances newspaper and magazine content by automatically tagging content with entity information from WikiData and IPTC Mediatopics. Content is enriched and exported in structured XML or JSON formats, ensuring that it becomes more discoverable, semantically meaningful, and ready for multi-channel distribution. This automated augmentation process increases efficiency and accuracy while preserving the original content structure, enabling publishers to unlock the full value of content.
Smarter Search with a RAG Chatbot
The Digital Archive integrates a Retrieval-Augmented Generation (RAG) chatbot, allowing users to search content and receive precise answers drawn exclusively from the archive. Each response includes source attribution, supporting pro-rata insights and ensuring the value of original article is recognized. By combining AI search with controlled access, the system delivers fast, reliable, and trustworthy results, giving editorial teams and readers confidence in both the information and its provenance.
AI Summarization and Translation
Content elements can be automatically summarized using extractive and abstractive techniques and translated into multiple languages without altering the XML or JSON structure. This ensures the original formatting, metadata, and tagging remain intact while making the content easier to access, share, and repurpose across different platforms. Customers benefit from faster workflows, higher engagement, and broader reach, all while maintaining complete control over the quality and structure of their media content.
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Frequently Asked Questions - AI Enrichment
What is AI Integration / AI Enrichment and what does it do?
AI Integration (also referred to as AI Enrichment) uses advanced artificial intelligence to enhance your content. This includes metadata tagging, entity recognition, smart search, summarisation, translations, and more turning raw editorial material into structured, semantically rich output that’s easier to use across platforms.
What types of content can be enriched and in what formats is the enriched content delivered?
Our AI enrichment works on newspapers, magazines, articles, and other editorial content. However it can also be used on audio and video content once converted with speech-to-text. The AI automatically identifies entities such as people, locations, organizations, and topics, and enriches the content with structured metadata. The enriched output is delivered in XML or JSON, making it fully machine-readable and ready for integration into digital archives, CMS platforms, search tools, and AI-driven applications.
What can I do with the structured XML / JSON output?
Once enriched, your XML/JSON content can be used to:
Power AI search and discovery tools, like chatbots
Integrate into content management or digital archive systems
Support automated translation, summarisation, or analytics workflows
Enable smart syndication and multi-platform distribution.
Which languages does the AI model currently support, and can new languages be added?
The AI enrichment models currently support German and English, providing high-quality tagging, summarisation and semantic analysis in both languages. If you need support for additional languages, please let us know. We can expand language support based on your content and workflow needs.
What is the difference between a RAG chatbot an LLM Model like ChatGPT?
A RAG (Retrieval-Augmented Generation) chatbot answers questions only using your own trusted content, retrieving relevant documents first and then generating answers based on those sources. ChatGPT, by contrast, is a general-purpose model trained on a broad mix of public data and does not have inherent access to your private content unless explicitly connected. This makes a RAG chatbot more accurate, controllable, and transparent for professional and editorial use, as answers are grounded in your own data with clear source attribution.
Is your AI system open or closed? How is data safeguarded?
Our AI system is closed and fully controlled within our own software environment. Client data is not shared, reused, or exposed to public AI models. This ensures data security, confidentiality, and compliance, making the solution suitable for sensitive editorial archives and proprietary content.
Can your AI enrichment handle translations, and which languages are supported?
Yes, we integrate with DeepL via API to provide high-quality translations. Any language that DeepL supports can be translated using our system, allowing AI-enriched content to be automatically converted into multiple languages while preserving structure and metadata.