AI in Action Technology
Talk to Your Graph Client for GraphDB
Learn how to develop a Talk to Your Graph (TTYG) client by integrating GraphDB and the OpenAI Assistants API
Pavel MihaylovAI in Action
Pavel Mihaylov
AI in Action Technology
How Far We Can Go with GenAI as an Information Extraction Tool
How we used Ontotext GraphDB and LLMs to improve CV selection
Anna Aksenova
Petar Mitankin
Filip Dimitrov
Stefan Nikolov
AI in Action Technology
My Dear Watson, it is Great to Have Someone to Talk to
Join us to learn how we empower users to sift through a large pool of data with the help of a trusted assistant – the GraphDB 10.8 Talk To Your Graph agent.
Nedelina Mitankina
Andrey Tagarev
AI in Action Technology
Talk to Your Graph Client for GraphDB
Learn how to develop a Talk to Your Graph (TTYG) client by integrating GraphDB and the OpenAI Assistants API
Pavel Mihaylov
AI in Action Technology
How Far We Can Go with GenAI as an Information Extraction Tool
How we used Ontotext GraphDB and LLMs to improve CV selection
Anna AksenovaPetar MitankinFilip DimitrovStefan Nikolov
AI in Action Technology
My Dear Watson, it is Great to Have Someone to Talk to
Join us to learn how we empower users to sift through a large pool of data with the help of a trusted assistant – the GraphDB 10.8 Talk To Your Graph agent.
Nedelina MitankinaAndrey Tagarev
AI in Action Technology
Semantization of Regulatory Documents in AECO
Learn how knowledge graphs combined with the latest natural language processing technologies aid regulatory information extraction and processing from unstructured data.
Arkadiusz Chadzynski
Nataliya Keberle
AI in Action Informational
Advancing Automatic Knowledge Extraction with PubMiner AI
PubMiner AI aims to help researchers in the biomedical domain overcome the challenges in automatic knowledge extraction from large volumes of scientific publications.
Ivelina Nikolova
Katerina Serafimova
AI in Action Technology
Leveraging Ontotext’s Eligibility Design Assistant for Effective Patient Population Selection
Combining highly normalized knowledge graphs with large language models for quick and reliable selection of clinical trial eligibility criteria
Ivelina NikolovaKaterina Serafimova
Georgi Iliev
Todor Primov