Infrastructure that makes AI possible.
Scalable pipelines, cloud migrations, data lakehouses, and MLOps. We build the foundation your AI and analytics stack needs, from ingestion to transformation to the platform layer.
Legacy systems are rarely AI-ready.
Data quality issues are common, and without the right architecture, analytics and AI applications simply cannot run reliably.
Assess the data landscape and AI-readiness, with concrete recommendations on where to start.
Guide platform decisions and architecture design for long-term scalability.
Enable and challenge legacy systems for better data management and AI integration.
Transform, clean, and enrich data on the best-suited platform, cloud or on-premises.
Enable internal teams and hand over architecture, pipelines, and processes.
Your data on AWS, Azure, GCP, or Databricks, cleanly structured and documented.
Scalable, tested, maintained pipelines, not scripts held together with hope.
The setup to deploy, monitor, and retrain your models reliably.
End-to-end ML development, from raw data ingestion to a usable interface.
Data platform for a GenAI product
An InsurTech building a GenAI product needed a solid data foundation. We designed the vector store architecture and data platform on AWS with production-speed retrieval. The early engineering decisions meant they did not have to redo them three months in.
Data lakehouse on Databricks
The same company had data scattered across systems with no clean way to work from it. We built a full data lakehouse on Databricks covering architecture, pipelines, transformations, and the MLOps layer. Their team went from fighting data plumbing to shipping models.
Cross-cloud analytics pipeline
An industrial robotics company had data across three cloud environments with no unified view. We built a pipeline across AWS, Azure, and Databricks feeding a single analytics layer. Production monitoring went from fragmented dashboards to one coherent view.
LLM deployment on Swiss Cloud
A FinTech in a regulated environment needed a custom LLM deployment within Swiss data borders. We deployed the full stack on Infomaniak Swiss Cloud, covering model infrastructure, data pipeline, and compliance layer.
Competitor pricing intelligence
A retailer wanted to stop pricing based on last week's competitor data. We built a pricing intelligence pipeline on Google Cloud that processed competitor data daily. The pricing team had live input instead of weekly reports.
Let's talk through your situation.
Fredrik Moeschlin CEO & Founder
