Named Entity Recognition (NER)
Extract critical information from unstructured text. We build high-accuracy NER datasets to train models that identify people, places, organizations, and custom entities.
Core Capabilities
Advanced technology built for enterprise scale.
Custom Entity Tagging
Labeling domain-specific entities beyond standard categories (e.g., medical symptoms, legal clauses, product SKUs).
Relation Extraction
Annotating relationships between entities (e.g., 'Person A is the CEO of Company B') for knowledge graphs.
Entity Resolution (Linking)
Disambiguating entities by linking them to specific database entries or knowledge bases (e.g., Wikidata).
Coreference Resolution
Identifying when multiple expressions refer to the same entity across a long document.
Nested Entities
Annotating complex structures where one entity is contained within another (e.g., 'University of [California]').
Multilingual NER
Building consistent extraction datasets across multiple languages and character sets.
Proven Applications
See how industry leaders are leveraging our solutions in production environments.
Discuss Your Use Case
Financial Research
Extracting company names, ticker symbols, and monetary values from earnings reports.
Healthcare NLP
Identifying patient symptoms, drug dosages, and anatomical references in clinical notes.
Legal Contract Analysis
Highlighting parties, dates, jurisdictions, and liabilities in legal documents.
Media & News
Tagging people, locations, and events to improve search and recommendation engines.