
Whether during creating market reports in a venture firm or collecting target information about chemical compounds in academia, researchers, analysts, and data scientists face routine manual tasks.…

Whether during creating market reports in a venture firm or collecting target information about chemical compounds in academia, researchers, analysts, and data scientists face routine manual tasks.…
Core product: Open-source information-extraction models and a composable IE platform (NER, relation extraction, Text→JSON, classification)
Deployment: Supports private/on‑prem and CPU/edge deployments
Team size (evidence): 6 employees (snapshot)
Funding signal: Multiple early rounds and grant support; investors reported include Ukrainian Startup Fund and Google
Registered as Knowledgator Engineering Ltd., London, UK (privacy policy)
Information extraction from unstructured text into structured/tabular databases for research, analysis, and data engineering workflows.
Machine learning / Information extraction / NLP
Crunchbase lists a funding event dated May 15, 2025; company reported to have multiple rounds (total across five rounds referenced)
“Reported investors include the Ukrainian Startup Fund and Google; company has received early-stage funding and grant support”
We are looking for an experienced C++ Developer who will work on performance optimization and deployment of AI models.
About us:
Knowledgator is an open-source ML research organization dedicated to advancing human knowledge through the development of foundational encoder-based models for information extraction. We are core contributors to GLiNER, a leading zero-shot Named Entity Recognition (NER) framework. Our development of GLiNER.cpp has significantly improved the efficiency of running NER models in various deployment scenarios.
Requirements:
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