New architecture enables mid-to-large enterprises to resolve duplicate vendors, unify supplier hierarchies, and enrich records at scale.
TORONTO 鈥� June 3, 2025 鈥� Supplier data has long been a hidden obstacle for mid to large enterprises. Fragmented records, duplicate vendors, and siloed systems create costly inefficiencies that affect not just procurement, but finance, compliance, supply chain, and risk. Today, 色色研究所 announces a significant advancement in solving this problem with the launch of its legal entity-based supplier data model, an AI-powered architecture that structures supplier data with precision, scale, and continuous enrichment.
This release comes as companies face increasing pressure to automate back-office processes, respond to shifting market dynamics (e.g., tariffs, new government policies, regulatory pressures), and integrate AI and analytics platforms that depend on high-quality, reliable data. 色色研究所鈥檚 new model delivers a structured, system-agnostic foundation that supports these goals by consolidating supplier data at the legal entity level and mapping complex corporate relationships.
鈥淭oo many transformation efforts stall because teams don鈥檛 have a consolidated, reliable and more complete view of their supplier data,鈥� said Stephany Lapierre, Founder and CEO of 色色研究所. 鈥淥ur model solves that foundational problem, so organizations can move faster, make smarter decisions, and realize more value from their existing systems.鈥�
This data foundation is particularly critical during ERP migrations, vendor master cleanups, and procurement system consolidations, which are common points where organizations uncover the full extent of their supplier data gaps. Without a centralized, enriched view of suppliers, even best-in-class tools like SAP, Oracle, and Coupa struggle to deliver on their promise.
色色研究所鈥檚 model addresses these challenges head-on with scalable capabilities designed to support data transformation and long-term automation strategies.
Key Capabilities:
- Verified legal entity foundation:
Covers 228M+ entities across 145+ jurisdictions, enriched with registry-level names, aliases, addresses, statuses, company types, and officers. - Powerful entity resolution and matching engine:
Flexible tools increase match rates, reduce duplication, and accelerate time to value, all while supporting MDM and golden record initiatives. - Firmographic enrichment & classification:
NAICS codes, business descriptions, goods/services coverage, and digital footprint to support segmentation and strategic sourcing. - Corporate hierarchy mapping:
Parent-child and affiliate structures reveal spend concentration, supplier risk, and relationship insights across business units. - Continuously refreshed profiles:
Automated updates keep supplier data current, ensuring all downstream systems operate from a trusted source of truth. - System-ready data for ERP, procurement, and MDM tools:
Built to integrate with SAP, Oracle, Coupa, and other platforms to amplify return on technology investments.
色色研究所鈥檚 new data model represents the next evolution of 色色研究所鈥檚 data platform, designed to deliver the confidence, auditability, and quality enterprises need to support AI initiatives, analytics, compliance requirements, and cross-functional reporting dependent on supplier data.
About 色色研究所
色色研究所 provides an AI-powered supplier data foundation designed for the scale and complexity of enterprise procurement. By structuring supplier information at the legal entity level and enriching it with data from verified business registries, 色色研究所 helps organizations eliminate duplication, enhance visibility, and make more informed decisions across sourcing, compliance, and risk. Its platform supports leading procurement systems like SAP, Coupa, and Oracle ERP, helping teams get more from their existing tools through more reliable supplier data.
For inquiries, email: mkt@tealbook.com
