Fairmarkit’s machine learning software uses our customers’ procurement data to make more informed suggestions over time. The more procurement sources through the platform, the more intelligent and efficient its solutions.
Initially, Fairmarkit relies on historical transaction data and buyer behavior to recommend vendors and works across procurement categories and taxonomies. The platform finds patterns and opportunities customized to your unique sourcing needs. With every transaction, it continues to collect and analyze data in a structured format. Fairmarkit compares an organization’s procurement information with our vendor database to consistently deliver the best possible sourcing options. Over time, the system becomes more accurate and efficient for buyers and vendors alike.
At its core, the Fairmarkit platform offers solutions in the following areas:
- Automated Data Communication – Reduces the need for manual double keying and improves communication across departments
- Automated Vendor Recommendations – Auto-populates 10+ relevant vendors, saving the time spent looking in a P2P system or searching online for an item or service
- Automates Request for Quotes (RFQs) or Request for Services (RFSs) – Streamlines the collection and review of competitive bids through a structured process
- Metadata Intelligence Gathering – Enables our customers to assess their performance in real-time. Most companies don’t receive value from their own internal data, much less from their tail spend data. Fairmarkit turns data into actionable insights and creates easy-to-read visualizations for key areas of performance. With Fairmarkit, procurement can reliably measure success in areas such as buyer performance, department activity, vendor performance and consolidation, compliance and purchasing analysis.