[ Antcluster for Automotive ]
Quality records, supplier data, production logs — one continuous map.
Example query
"Compare defect rates across supplier batches for the last six months, broken down by plant and component family."
Your schema · one Topology Graph
Source systems
QMS · Supplier · MES · PLM
Join correctness
Cross-system query
Sub-minute
[ One graph ]
Every Automotive system → one queryable topology
Antcluster ingests each source database, discovers cross-system join paths automatically, and unifies them into one Topology Graph — no bespoke ETL pipeline required.
The data problems Antcluster solves in Automotive
Supplier batch correlations live in five systems
Antcluster federates QMS, supplier data, and production logs into one Topology Graph so defect-rate analysis runs as a single natural-language query.
Naive LLM joins produce plausible but wrong defect numbers
Curve-Context Join Discovery validates every join with mutual-information thresholds. Join correctness: 61% (naive LLM) → 96% (graph-guided).
Recall and warranty investigations require schema archaeology
Antcluster maintains chain-of-thought evidence trails for every traversal — every join, every value, every aggregation is logged immutably for audit.
Questions teams ask Antcluster
- Defect-rate comparisons across supplier batches by plant and component
- Warranty claim correlation with supplier batch and production-line metadata
- Recall root-cause investigation joining quality, supplier, and PLM data
- Supplier scorecard aggregation across plants and quarters
Further reading
See Antcluster on your Automotive data
30-minute live demo on a sample of your real database. Read-only, air-gapped, no setup required.
Book a demo