Material Finder

The challenge today

Sourcing decisions still run on PDFs and phone calls

For Tier-1/-2 suppliers and OEM engineering teams, sourcing a material that fits a specific application or OEM requirement typically begins with a manual search: gather data sheets from candidate manufacturers, request the latest revisions, normalise the different formats by hand, and build a comparison spreadsheet that may take a week to assemble. Once that spreadsheet exists, it is already out of date — and it lives in one engineer's folder, invisible to the next team facing a similar question.
Even when a material looks promising, the next question — is it already approved for the relevant OEM specification? — sends you back to the manufacturer's sales contact, into another round of email exchanges, and possibly into an unnecessary re-qualification cycle. Across hundreds of materials in an active portfolio, the cumulative cost in engineering time, missed alternatives, and delayed decisions is substantial.

Search across the network

Search across the network — find materials from raw material manufacturers and compounders in a single, unified database

Filter against your actual requirements

Filter against your actual requirements — specification, application, cost band, sustainability profile, processing parameters

Compare on standardised data

Compare on standardised data — TestID-referenced properties make candidates directly comparable, not approximately comparable

Use natural-language search

Use natural-language search — describe what you need in plain language, with AI-assisted TestID resolution

See approval status

See approval status — identify materials already approved against the OEM specifications you work with

Share findings with your team

Share findings with your team — discoveries become a shared resource, not an individual spreadsheet

Search and filter the network

The Material Finder draws on a structured network of materials maintained by raw material manufacturers and compounders. Search by name, application, property range, or specification reference. Filter by attributes that matter for your project — sustainability profile, processing characteristics, cost band, regional availability. The result is not a list of links to manufacturer PDFs, but a structured set of candidate materials with comparable underlying data.

TestID-based comparability

The technical comparability problem in materials sourcing is well known: two manufacturers may report what looks like the same property — tensile strength, for instance — but the underlying tests differ in specimen geometry, conditioning, strain rate, and acceptance criteria. The values are not directly comparable, and someone has to do the reconciliation work.
Where material data in the network is TestID-referenced, that work is already done. The same TestID means the same test — same specimen, same conditions, same parameters. Your comparison is between equivalent measurements, not between numbers that happen to share a label.

Natural-language search

Describe what you need in plain language — "a flame-retardant polyamide for under-the-hood applications, approved for Volkswagen, with low water absorption" — and the Material Finder resolves your description against the TestID system to return matching materials. The feature is currently in active development and improvement; the underlying TestID structure means resolution is grounded in defined methodologies, not in fuzzy keyword matching.

Approved-material visibility

When a material has been formally approved against an OEM specification — Volkswagen Produktfreigabe, BMW Produktfreigabe, Mercedes Produktfreigabe, and others — that approval is visible in the Finder. Materials already qualified against the spec you need surface ahead of candidates that would require a fresh qualification cycle. The path from found to usable gets shorter, sometimes drastically.

For material engineers and product development

Structured comparison replaces manual spreadsheet assembly; comparable property data across manufacturers, not approximations; faster identification of alternative materials when a primary candidate fails qualification or pricing changes.

For procurement and sourcing

A current view of the supplier landscape for any given material requirement; visibility into pre-approved alternatives that shorten qualification cycles; reduced dependency on individual sales-rep relationships for routine technical-fit screening.

For engineering and R&D leadership

Cumulative knowledge about the supplier landscape becomes a team asset rather than individual tribal knowledge; sourcing decisions can be supported by data the entire team trusts; the same discovery layer scales across projects and product lines without proportional engineering effort.