Examples¶
Bauplan performs many tasks typically handled by dedicated data platform teams—like managing infrastructure, versioning data, and orchestrating complex workflows. By providing these capabilities out of the box, Bauplan unlocks simplicity, reproducibility, and speed for scenarios such as deploying ML models, building feature stores, running data quality checks, serving real-time dashboards, and managing complex data transformation pipelines.
Serverless data product with built-in quality checks using Lambda and Bauplan.
Build a RAG system with Pinecone and OpenAI over StackOverflow data.
Medallion Architecture + WAP Pattern
End-to-end data engineering repo using Mage & the medallion architecture.
From unstructured to structured data with LLMs
Convert PDFs into structured, analyzable tables using LLMs.
Playlist recommendations with MongoDB
Embedding-based recommender system for music playlists.
Orchestrated WAP pattern for ingesting parquet files to Iceberg tables.
PDF analysis with bauplan and OpenAI
Analyze PDFs using Bauplan for data preparation and OpenAI’s GPT for text analysis
ML Model Training and Deployment Pipeline
End-to-end ML pipeline for predicting taxi trip tips.
Product matching across e-commerce catalogs using LLMs.
Implement data quality checks using expectations.
Build near real-time analytics pipeline with WAP pattern and metrics visualization.
Build an interactive dashboard to visualize taxi pickup locations in NYC.