Healthcare AI · Radiomics · RWE
From Omics Data to Predictive RWE Models
How reproducible radiomics, multi-omics and federated learning pipelines turn complex medical data into validated insights.
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With over 10 years of experience in the data space, our company has solved complex challenges across AI, data engineering and enterprise integration. Here, we present selected problems we have resolved that may be relevant to other organizations.
Data engineering · M&A integration
Solving the Post-M&A Master Data Bottleneck
How a deterministic and AI-assisted entity resolution pipeline harmonizes SAP, Dynamics and Salesforce customer data.
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Healthcare AI · Privacy-preserving ML
Breaking Data Silos in Pharma
How federated learning enables multi-center real-world evidence without moving raw patient data.
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Fraud detection · Machine learning · Risk architecture
From Real-Time Fraud Detection to Bottom-Line ROI
How streaming machine learning, graph analytics and financial utility metrics protect revenue without adding friction for legitimate customers.
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Agentic AI · Insurance · Claims automation
Agentic AI for Compliant Claims Processing
How LangGraph, retrieval-augmented workflows and human oversight turn complex claims into transparent, auditable decisions.
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Data engineering · Databricks · Azure
Optimizing Enterprise Workloads on Databricks
How an orchestrated medallion architecture turns heterogeneous structured and unstructured data into a governed source of truth for Power BI.
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Sales intelligence · Churn prevention · Machine learning
Predictive Sales Intelligence and Churn Mitigation
How external market signals and internal account data help revenue teams identify growth opportunities and act earlier on churn risk.
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Enterprise AI · SAP · Azure architecture
A hybrid BTP/Azure architecture for agentic AI integration into SAP
How a Clean Core architecture combines SAP BTP, Azure Container Apps and LangGraph to categorize complex support tickets.
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