What is NER?
Named Entity Recognition (NER) locates and classifies named entities into predefined categories such as persons, organizations, locations, dates, and monetary values.
It's used in compliance, knowledge graphs, and business automation to extract structured data from documents and communications, enabling faster analysis, better insights, and automated workflows.
- Document Processing
- Classification
- Structured Data
- AI-Powered
Applications
Named Entity Recognition powers a wide range of industry-specific solutions
Legal Document Analysis
Automatically extract parties, dates, obligations, and clauses from contracts and legal documents for faster review and compliance.
Resume Parsing
Identify skills, experience, education, and contact information from resumes to streamline recruitment and candidate matching.
Financial Report Tagging
Market Basket AnalysisExtract company names, ticker symbols, financial metrics, and dates from earnings reports and financial statements.
Medical Record Extraction
Identify patient names, diagnoses, medications, procedures, and dates from medical records for better healthcare analytics.
Tools We Use
Industry-leading visualization and analysis tools to explore your data
🔬
SpaCy
Industrial-strength NLP library with pre-trained models
🐼
BERT
Bidirectional transformer models for contextual understanding
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Hugging Face Transformers
State-of-the-art pre-trained models for various NER tasks
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Custom-trained CRF
Conditional Random Fields for domain-specific entity recognition
Case Study Energy Consumption Forecasting
Energy consumption forecasting improved grid efficiency by 22%, reducing waste and optimizing power distribution across the network
+22%
Efficiency Improvement
-18%
Energy Waste Reduction
96.8%
Forecast Accuracy
48hrs
Forecast Horizon
24-Hour Energy Forecast (MW)
- Predicted
- Actual
Forecast with Confidence. Act with Clarity.
Master temporal patterns, detect anomalies, and predict future trends with industry-leading time series analysis techniques.