Named Entity Recognition, sentiment and emotion analysis, document intelligence and classification, question answering systems, text summarisation, language translation and localisation, and custom NLP model development trained on domain-specific data. A production NLP application is LexOps AI, which uses NLP to extract legal clauses and classify contract terms across MSAs, SOWs, and NDAs.

BERT, RoBERTa, and DistilBERT via Hugging Face Transformers; domain-fine-tuned LLMs (GPT-4, Claude, LLaMA); spaCy for NER and dependency parsing; NLTK and Gensim for topic modelling; Azure AI Language for text analytics and entity recognition; AWS Comprehend for custom classifiers; Google Cloud Natural Language API; and FastAPI with Azure ML or SageMaker for production deployment.

Yes. Kernshell builds domain-specific NLP for legal document analysis (contract clause extraction and risk classification in LexOps AI), clinical NLP (extracting structured data from unstructured medical notes, ICD-10 coding assistance), and manufacturing (technical manual parsing, quality report classification, and automated CAPA narrative generation for ETQ Reliance integration).