As an AI-native platform, Levelpath faces this challenge head-on. From the start, Levelpath has been built with the assumption that generative AI and its descendants were going to become a massive force for increasing productivity. To fully leverage the benefits of AI in relation to data management, Levelpath has placed significant efforts on supporting compliance, stewardship, and metadata context throughout the supplier relationship.

To start with, Levelpath’s data schema is defined through Data Manager, an administrative tool designed to support defined and predictable data schemas. Procurement departments want to ensure that they can maintain consistent standards for all relevant supplier and sourcing data across thousands of suppliers. The honest truth is that many supplier fields that are necessary for an AI-enabled world have been ignored in legacy ERP and P2P solutions over the past decade or more in the transactional rush to get work done. Data Manager provides an opportunity to fully define supplier, sourcing, and contract terms and to enforce them.

Used consistently, this approach reduces data gaps and eliminates ambiguous supplier records that can confuse and slow down sourcing efforts. It also fixes typos and unclear records. Without this cleanup, companies end up with duplicate records and non-standard field usage that create too many suppliers, excess fields, and messy categories, making it hard for procurement teams to stay organized.

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