Data Science & GenAI

From raw data to decisions — classical ML and Generative AI

Data science is where business questions meet data. We help you frame the right problem, explore your data, and build models that deliver measurable value — whether that is a forecast, a recommendation, a computer-vision system, or a Generative AI assistant grounded in your own knowledge.

Every project runs as a disciplined experiment: clear success criteria, tracked runs, and honest evaluation against a production baseline. We log parameters, metrics and artifacts in MLflow so results are reproducible and ready to hand off to engineering.

Our team works with Python, scikit-learn, PyTorch, XGBoost, Optuna and Ray, foundation models and LLMs via Mosaic AI, and accelerates discovery with MLflow and AutoML on Databricks.

What we deliver

• Exploratory Analysis & Predictive Modeling - EDA, statistical summaries and predictive and forecasting models that move you from "what happened" to "what is likely next" for demand, risk, churn and pricing.
• Recommendation, Vision & Behavior - recommendation engines, computer-vision systems (image recognition, object detection) and user-behavior analytics that surface patterns and anomalies.
• Generative AI & LLM Solutions - retrieval-augmented assistants, summarization and extraction built on foundation models, with the same grounding and evaluation rigor as classical ML.
• Experimentation & Hyperparameter Tuning - structured experimentation, automated hyperparameter search and model evaluation, so the best configuration wins on evidence rather than intuition.