Delivered systems, measurable outcomes
Production systems and applied AI engagements across healthcare, finance, public administration, publishing and telecommunications.
The portfolio includes production-grade systems and applied AI engagements evaluated against defined business outcomes. Engagements whose result metric is marked Pending — engagement in progress are ongoing and are identified transparently below. From real-time claim scoring and NLP-driven investment signals to petabyte-scale record linkage, the work spans regulated industries and demanding data environments. Confidential engagements are named by sector only.
ML-driven approval prediction for dental prosthesis claims
A real-time Kubernetes ML platform delivered to multiple AOK health insurers automates straightforward approvals and flags complex cases for human review, with data protection and regulatory compliance embedded by design.
NLP-enhanced stock performance forecasting
Analysis of over 90,000 earnings-call transcripts generated communication-derived features that, combined with financial fundamentals, produced a differentiated, data-driven trading strategy.
End-to-end record linkage pipeline
A distributed XGBoost-on-Spark system linked internal records with heterogeneous external sources at petabyte scale, streamlining manual review for the prosecution of fraudulent entities.
GenAI for text summarization in German
An economical, automated summarization platform met the client’s editorial quality benchmarks, reduced costs and enabled staff to focus on higher-value editorial work.
Machine learning-driven customer segmentation
Actionable customer segmentation clarified market potential and surfaced profitable expansion opportunities, supported by a data-governance framework for targeted marketing and sustained growth.
Snowflake data platform for credit analysis and portfolio management — In progress
A test-covered Snowflake and dbt foundation consolidates security issuers, identifiers, analysts, coverage and securities into a governed, fully historized source of truth for credit analysis and future ML use cases.
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