Overcome poor data quality
Tamr’s machine learning-based approach leverages all available data to make the best possible classification recommendation, lowering the bar on the data you need to capture from buyers.
Visibility across all sources
Tamr gets smarter as it sees more data, enabling you to cost-effectively incorporate all your spend data sources.
Always-on data pipelines, across all of your internal and external data sources, mean spend analytics reports continue to update as your supply chain moves.
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Inputs can include ERPs, procure-to-pay, pCards, spreadsheets and external data
Human guided machine learning including classification models trained with examples
Unified data with classification results enriching source data
Improved analytic insight
Move beyond the hype
Tamr focuses on cleaning up your data so you can get the foundational spend analytics right before attempting to take on more complex, predictive analytics.
Learn how Societe Generale cleaned up their data and gained visibility into their spend in under 2 months.
Speak the same language as your data
Tamr is capable of learning how to classify data into any multi-tier hierarchy provided. Once it learns, automated data feeds can be established to move new spend through the system.
Watch how Tamr enabled data-driven procurement for GE.