biomedical language processesing. powered by AI. designed for pharma.

Built and trained for pharma business use cases, tellic’s cutting edge automated machine learning text curation engine lets you process billions of text documents with PhD level accuracy

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Document Classification

Dozens of processing stages enable you to use text from many formats and systems, filtering out non-scientific documents, and categorizing by business domain

Employing a combination of dictionary terms and hand coded rules, most search solutions for biomedical data lack the ability handle different structures of text data and therefore fail to deliver useful results, and lack utility for scientists to focus in on what’s most important to them. tellic’s machine learning and AI technology extracts common terms and relationships from biomedical text then to help scientists:  1. Find a greater set of relevant documents by extending the reach of search terms by identifying synonyms and understanding the context a term is used.  2. Ignores sets of irrelevant documents by using the context a term is used to identify false positives results  3. Enabling scientists to quickly drill down to find the results most documents most relevant to them using customized labels trained on their organizational language

Employing a combination of dictionary terms and hand coded rules, most search solutions for biomedical data lack the ability handle different structures of text data and therefore fail to deliver useful results, and lack utility for scientists to focus in on what’s most important to them. tellic’s machine learning and AI technology extracts common terms and relationships from biomedical text then to help scientists:

1. Find a greater set of relevant documents by extending the reach of search terms by identifying synonyms and understanding the context a term is used.

2. Ignores sets of irrelevant documents by using the context a term is used to identify false positives results

3. Enabling scientists to quickly drill down to find the results most documents most relevant to them using customized labels trained on their organizational language

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Metadata CATALOG

Automation and processing uses machine learning and AI to generate a metadata catalog that brings together all 360 degrees of your structured and unstructured data sources

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Cognitive biomedical search

Machine learning ranks documents most relevant to your scientists

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PHARMA Knowledge graph

Fully automated AI pipeline constructs and grows a knowledge graph from your pharma R&D data

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