Flexor
Ella Neeman is an experienced NLP Researcher currently working at Flexor, where efforts focus on enriching data pipelines and analytics through unstructured textual data. Previously, at The Hebrew University of Jerusalem, Ella contributed significant research in collaboration with Google Research, developing a novel method for Question Answering models. Ella's expertise also includes data science research at Synamedia, where machine learning models were utilized to detect and classify credential sharing activity. Early career experience involved managing consultation processes for large organizations at Insights.US and producing news content at Galei Tzahal, where recognition was received for excellence in coordination and editing. Ella holds a Master's degree and a Bachelor's degree in Computer Science, both from The Hebrew University of Jerusalem.
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Flexor
Flexor is a Transformation Layer for Unstructured Data. We are changing how companies capitalize on their most significant untapped data source: unstructured textual data. We empower data practitioners to harness LLMs to transform raw textual data into powerful signals. By bridging the gap between structured and unstructured data, we help teams supercharge their data ecosystem: with Flexor, anyone can transform text into product features, automated workflows, and analytics processes - blazingly fast.