Case Study
Sector
Aerospace & Defense
Products
Thermal systems, landing gear
Use Case
Enterprise Strategic Sourcing, Direct Materials
01
Background
This customer manages direct materials sourcing across a combined catalog of roughly 80,000 active parts. Like many complex OEMs, its part data, sourcing history, and supplier fit information were split across drawings, ERP records, and purchasing history—separate systems that had to be reconciled by hand every time a sourcing manager needed to act.
02
Challenge
The customer's sourcing team faced a structural bottleneck common to complex OEMs managing direct materials at scale:
Fragmented part data: Part specifications, sourcing history, and supplier capability information lived in separate systems, requiring hours of manual work to reconcile before a sourcing manager could act.
Manual research bottleneck: Identifying part similarity and consolidation opportunities across the catalog required time-intensive manual review, and non-obvious connections between parts were easy to miss.
High bar for AI adoption: The customer had historically been cautious about deploying AI tools in its sourcing operations. Any new technology had to meet a high bar for security and compliance before broader adoption.
03
Solution
The customer partnered with Paperless Parts to launch a proof-of-concept covering active sourcing analysis for 2,500 priority parts, with its full 80,000-part catalog processed as the reference library to strengthen similarity matching and supplier recommendations across every query. Paperless Parts' FedRAMP Moderate Equivalent infrastructure met the customer's security and compliance bar for testing AI in a live sourcing environment.
AI-Powered Part Characterization
Radar extracted and indexed materials, geometry, process requirements, and tolerances across the customer's priority parts, making previously siloed part data searchable for the first time.
Similarity Matching and Consolidation
Radar's similarity matching surfaced consolidation opportunities across the customer's catalog that would not have been found through manual review, including non-obvious connections between parts made through different processes.
Supplier Recommendations Mapped to Spend
Radar joined supplier spend data against extracted part data, giving the customer a cross-referenced view of parts and sourcing history to inform supplier recommendations.
04
Results
The customer processed the first tranche of 1,200 files from its thermal systems product line in May 2026.
97% Reduction in Sourcing Research Time: A sourcing workflow that previously required six hours of manual research now takes ten minutes.
New Consolidation Opportunities Surfaced: Using Radar's output, the customer made a group of cast parts with non-obvious similarities across its catalog and sent a targeted RFQ package to a regional casting supplier. The supplier confirmed every part was within their capability: "These parts are perfect."
Cross-Functional Buy-In: Paperless Parts presented results on-site to a cross-functional group spanning Strategic Sourcing, NPI, Supplier Development, and Procurement at both central sites, generating strong alignment across the group.
05
Looking Ahead
The customer is targeting completion of a 45-50 part make-to-buy transition at its primary site within Q2, compressing an 18-month effort into a single quarter. Next steps include expansion to a second site with cross-site supplier consolidation analysis, assisting with re-quoting prior to LTA renewal to validate pricing rather than auto-renew, and support for new product introduction (NPI) part tranches as engineering's NPI workflow scales.
What once lived as disconnected part and supplier data is becoming a shared map for faster, more coordinated sourcing decisions across the enterprise.