Project semANT

We are developing new ways how to navigate, search, explore, visualize and analyze large collections of text documents. We are defining how digitized printed and handwritten documents will be used and accessed in the future.

Make sense of documents

Czech libraries and archives are home to a wealth of digitized documents, and we’ve seen significant strides in improving their online accessibility and search functions. However, the current full-text search, while adept at recognizing different word forms, lacks the ability to understand their meaning, making it a challenge to find documents on specific topics.

At semANT, we’re dedicated to simplifying the search process and improving the exploration of digitized documents, making it more intuitive and insightful for everyone.

We are working with
Processed document pages
Digitized pages in Czech libraries
Training text data
Cooperating libraries

We strive to make searching in libraries and archives more enjoyable and comprehensive, enabling discoveries through semantic search.

Our Goal

What are we working on

We are creating a next generation document access application incorporating advanced AI capabilities.

Semantic search

We are building semantic text embedding models for historic documents which allow us to retreive thematicaly relevant texts.

Adaptive search

Search results should adapt to current user goals and recent history. The search system should propose meaingfull query refinements and filters.

Question answering

Natural language interaction is the future. We strive to combine document retrieval with chatbot-like interface to efficiently anser user questions.

Topic discovery

Discover topics in collection of documents or search results. Tag user topics, analyze and shere them.


Visualize topics developing in time, topic contexts, topic relations and content.


Seamlessly search across documents from many languages, and explore the documents in your language using state-of-the-art automatic translation.

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