Platform Engineering

Define the data & AI strategy, target architecture, and governance framework. We assess current systems, identify data sources (IT, OT, IoT), and design the foundation for streaming, lakehouse, and AI integration — secure, compliant, and future-ready.

Implement scalable data pipelines, real-time streaming infrastructures, and machine learning workflows. We bring models from notebooks into production, design lakehouse platforms (e.g. Databricks, Iceberg, Delta), and integrate AI into business applications.

Optimize pipelines, platforms, and models for performance, resilience, and cost-efficiency. Introduce MLOps pipelines for automated retraining, monitor data quality and drift, and ensure compliance.

Empower teams to own their Data & AI platform. We transfer knowledge on data engineering, ML Ops, and governance, establish best practices, and provide StarterKits and trainings so internal teams can extend and scale independently.

Unlock new business models with Data & AI. From predictive maintenance and data products to LLM copilots and agentic AI, the platform evolves into a driver of innovation and measurable business impact.