Machine Learning uses algorithms to learn patterns from data. Deep Learning uses neural networks for complex tasks like image/speech recognition. Generative AI creates new content (text, images, code) based on training data. We help you choose the right approach for your use case.

We follow a rigorous ML lifecycle including data quality assessment, feature engineering, model validation, cross-validation, bias detection, and continuous monitoring. We implement responsible AI practices to ensure fairness, transparency, and ethical deployment.

Timeline depends on data availability and complexity. Simple ML models can be deployed in 4-6 weeks. Enterprise-grade AI solutions typically take 3-6 months. We use agile delivery with working prototypes in 2-week sprints to show value early and often.