Agentic AI cuts OEM data extraction labor by 90%+
An agentic AI pipeline extracts equipment and package data from 750+ complex OEM PDFs across 40+ manufacturers, turning work that took weeks into minutes, in production today.
The Opportunity
A leading North American automotive data provider serves carmakers and insurers. Older systems and hand fed data made onboarding a new carmaker slow and added risk during the busiest release periods.
It needed clean, well governed, analysis ready data without all the manual effort.
The Transformation
An automated extraction pipeline parses complex OEM PDFs using Gemini and OpenAI models with unstructured.io, applies custom DSPy models trained on OEM specific layouts, and moves from ingestion to mapping to structured output.
The framework is designed to adapt as OEM formats keep changing.
Multi Model PDF Parsing
Gemini and OpenAI models, combined with unstructured.io, parse complex OEM PDFs that vary in version and format across more than 40 manufacturers.
OEM Specific Custom Models
Custom DSPy models are trained on each OEM's specific layout, instead of relying on one generic model to handle formats that don't look alike.
Automated Extraction Pipeline
Data moves through ingestion, mapping, and structured output automatically, replacing a process that used to be done by hand, one PDF at a time.
Built to Scale with OEM Formats
The framework is designed to adapt as OEM formats evolve, so new manufacturers and layout changes don't require rebuilding the pipeline from scratch.
Reduction in labor for extraction tasks
Tasks that used to take weeks now complete in minutes
Delivered via custom trained, OEM specific models
OEMs covered, all active US and Canada manufacturers