Unsupervised discovery
No predefined labels required - the API finds coherent topics directly from the content.
Surface emerging topics from unstructured text without predefined labels.
Talk to us about accessThe Topic Modelling API surfaces what people are actually talking about - without you having to define the labels in advance. It groups documents into coherent topics based on the language inside them, so you see narratives as they emerge, not after they break.
Unlike keyword monitoring, topic modelling captures themes that span many wordings, languages and outlets - giving you an honest map of the conversation around your space.
Common use cases:
Built and maintained by the Identrics applied AI team. Trained on human-in-the-loop data, benchmarked continuously, and shipped to you as a single, well-documented API.
No predefined labels required - the API finds coherent topics directly from the content.
Group documents that talk about the same thing even when they are written in different languages.
Track how each topic grows, shrinks and connects to others over time.
Receive human-readable summaries and key terms for each topic, ready to render in a UI.
POST a batch of documents covering the period or domain you want analysed.
Documents are embedded and grouped into coherent topics with descriptors and key terms.
Get back topics, document membership, volume and trend data ready for dashboards.
Every Kaspian enrichment ships as its own API, and they all share a common contract - so you can call Topics on its own today, or chain it with any of the others tomorrow to build a richer pipeline. No extra integration work.
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