Does your vendor really use learning AI to improve your data?

June 8, 2022 | Steve Griffiths

Artificial Intelligence (AI) is sweeping the software ecosystem, generating tons of buzz from customers and software providers alike. Today every company strives to have an intelligent capability that claims to transform data or automate tasks. It’s hard to distinguish if your application actually has an AI/ML-driven engine or if it’s just a BI tool with automation of manual tasks? Often, vendors claim to use Artificial Intelligence (AI/ML tool), where they might simply be using Business Intelligence (BI tools) or Automation (of manual tasks) to deliver some outcome to the user.  

In Procurement and Supply Chain, there are several areas that can benefit from AI/ML models. At Xeeva, we use true Artificial Intelligence, deep Machine Learning, and statistical models for several features, but the 4 key features are: –   

  • Enrichment 
  • Classification  
  • Item price comparison, trending, and benchmarking  
  • Intelligent Opportunities


Predictive analytics, benchmarking and forecasting, inferential analytics, all types of advanced analytics rely on more complex and deeper understanding of data that has been collected from multiple diverse sources and intelligently work together. Enriching customer data with 3rd party data and generating machine learning models is a way to understand and meet these complex analytical needs.  

Both the customer data and the 3rd party data that is used in the above analytics are a snapshot in time and therefore any insights generated using them will become stale unless the data is continuously refreshed and enriched with new learnings. Fresh insights need to be generated using this refreshed data on an ongoing basis. Machine learning is an area within computing that enables automation of data enrichment without manual efforts making the data more insightful and actionable for the types of analytics mentioned above. Xeeva will support a higher quality of enriched data, continuous enrichment of past data, faster data onboarding, and frequent data refreshes due to its reliance on deep ML-based continuous enrichment.  


You know that the software application is not using true AI if it is not continuously learning from the past classification, and not applying that learning to similar items.  If you have to manually refresh the classification of past items and suppliers on an ongoing basis the solutions are not based on true AI!   

AI learns from the classification applied to items in the training dataset, it continuously learns from the classification applied to added items and automatically categorizes that same item when it encounters it in the future. It also applies the learning to similar future items when added items are introduced into the system. A true AI-driven solution does not need to continuously classify the same or similar data repeatedly. True AI-driven solutions learn to apply the relevant classification to data that it has seen before.   

Item-Price comparison, trending and benchmarking 

Does your spend management solution constantly compare your commodity pricing to the commodity price in the market?  

An intelligent spend management solution utilizes its network of suppliers, clients, and independent 3rd party commodity data to continuously compare the price you pay for a commodity to what the industry is paying for that commodity. This item-level price comparison and benchmarking utilize a combination of AI, ML, and statistical models to give our customers more actionable alerts in a timely manner to maximize their negotiating power and potential saving opportunities. Intelligent tools like Spend Analytics also let you know about any discounts offered by our suppliers for certain categories and items such as packaging, abrasives, or a particular tool.   

Intelligent Opportunities  

Does your current spend management tool give you category-based and system-ranked savings opportunities based on your current spending patterns?  

Machine learning and statistical models constantly analyze the spend transactional data to generate and provide smart savings opportunities based on current contract terms and market trends in pricing. Once your data has been enriched and classified, Spend Analysis type tools can drive bottom-line savings and automate the routine tasks such as comparing supplier prices, identifying areas of large tail spend, allowing you to focus on strategic management of supplier relationships, pricing negotiations, wave planning of savings initiatives.   

Any true AI spend management tool should have the capabilities that use a combination of AI, ML and statistical modeling to provide ongoing enriched and classified data, deeper analytics, automation of repeated data refreshes. To learn how Xeeva’s Intelligent Spend Management tool helps you drive savings, schedule a DEMO today  

About XeevaXeeva is the leader in indirect spend management solutions that optimize the entire procurement process. With Xeeva’s data-driven spend management solutions, you can simplify, consolidate, manage, control, and conduct all spend-related activities in one place. Our end-to-end integrated cloud-based platform drives cost savings, performs data enrichment, increases visibility into spend, and adds efficiency gains throughout the procurement process. For more information, visit