Our models achieve 98% accuracy on Modern Standard Arabic and 95%+ on Saudi dialect. We handle Arabic's complex morphology, diacritics, root-pattern systems, and code-switching between Arabic and English. Our Arabic linguists continuously refine the training data for Saudi-specific expressions.

Yes. We integrate OpenAI GPT-4, Google Gemini, Anthropic Claude, and open-source models like LLaMA and Falcon. We handle prompt engineering, fine-tuning on your data, RAG (Retrieval-Augmented Generation) pipelines, and cost optimization for production workloads.

Our Arabic sentiment analysis achieves 95%+ accuracy on formal text and 90%+ on social media and dialect content. We continuously train on Saudi-specific datasets including Twitter/X, Google reviews, and customer service logs. Models handle sarcasm, negation, and mixed Arabic-English text.

Data security is paramount. We offer on-premise deployment for sensitive data, encrypt all data in transit and at rest, comply with Saudi PDPL and NCA standards, and can work within your VPC. We never use client data to train models for other clients.

Yes. While Arabic and English are our primary focus, our models support French, Urdu, Hindi, and other languages common in the Saudi market. We can build multilingual pipelines that detect language automatically and route to the appropriate model.

NLP models need periodic retraining as language evolves. We provide monthly accuracy reports, quarterly model updates, drift detection alerts, and continuous data pipeline monitoring. Our SFD Studio dashboard gives you real-time visibility into model performance metrics.