Atlas

Procurement intelligence for mapping merchant SKUs to credible upstream sourcing alternatives and comparing evidence-backed acquisition scenarios.

Applied AIProcurement IntelligenceProduct MatchingEvidence WorkflowsFull-Stack

Private repository · open-source planned

Case study

What this project demonstrates

Atlas is being built around the hard part of procurement intelligence: not merely finding a similar listing, but establishing enough identity, provenance, cost, and supplier evidence to compare sourcing decisions credibly.

Architecture

Merchant SKU → identity normalization → candidate sourcing discovery → evidence/provenance layer → landed-cost comparison → ranked acquisition scenarios

Engineering highlights

Maps merchant SKUs to candidate upstream sourcing alternatives using product identity and provenance signals.
Compares acquisition scenarios using landed cost, supplier evidence, and traceable sourcing context.
Designed as a usable product rather than a research-only matching experiment.
Source code is private during development, with open-source release planned after completion.

Boundaries / limitations

Still under private development. Public usage, benchmark claims, and source release will be added only after validation and launch.