Developer Builds AI-Powered MLOps Pipeline Using Google TabFM and Gemma 2B for EU Compliance

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A developer created Dataset Automator, a multi-agent MLOps platform submitted to Google Cloud's AllThingsAgenticHackathon, designed to transform tabular CSV or Excel data into production-ready machine learning models within 60 seconds. The system integrates Google TabFM, Gemma 2B, and Gemini 3.5 Flash alongside Neo4j GraphRAG to automate model training, generate executive financial reports, and produce EU AI Act-compliant cryptographic attestations. To manage costs, the platform uses a cascade routing strategy that directs 85% of tasks to the locally run Gemma 2B model at no API cost, reserving Gemini 3.5 Flash for complex reasoning tasks, achieving a claimed 125x cost reduction compared to using GPT-4 exclusively. The pipeline features a visual seven-node canvas with human approval gates at key stages, ensuring oversight and auditability throughout the process. Currently running locally on Streamlit, the application is designed for full deployment on Google Cloud Run and BigQuery.

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