Identity, capabilities, qualifications, experience, capacity, performance and risk — with source, date observed, method, confidence and verification status on every material attribute.
Supplier master data decays quietly: an attribute recorded years ago looks identical to one verified last week, so nobody can tell which claims are safe to rely on. SpiderNet stamps every material attribute with where it came from, when it was observed, how, how confident it is and whether anyone verified it — and never treats an AI inference as verified fact.
Identity, capabilities, qualifications, experience, capacity, performance and risk in one record.
Source, date observed, method, confidence and verification status on each attribute.
Expiry recorded where an attribute has one.
AI-inferred data is never treated as verified fact.
Every data point is classified — verified, declared, observed, inferred, outdated or contradicted.
No. AI-inferred data is a distinct classification and is never treated as verified.
Each carries its date observed, and expiry where applicable; outdated is one of the data classifications.
They can submit corrections through a data-correction link, which go to the vendor manager queue.
Extracts each requirement from the SOW with its type, importance and a citation to the page.
A requirement excludes a supplier only after a person confirms it is mandatory.
Specialised agents widen the candidate pool beyond the suppliers you already know.
Five separate matching layers, and every score opens onto its evidence.
See the complete product: problem, features, how it works and deployment.
Request a demo to turn a real statement of work into an evidence-backed supplier shortlist.