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Public Sector

Find More Prospective Suppliers & Drive Competitive Bidding


Government agencies are challenged with trying to find more prospective suppliers and drive competitive bidding. NAICS and SIC codes are not sufficient to describe the capabilities of a potential supplier, making it difficult to find the appropriate suppliers to bid on contracts. Each prospective supplier describes their capabilities differently and a simple keyword search will miss potential suppliers/bidders. Current search engines are insufficient in aiding analysts search for new prospective suppliers, as there are too many irrelevant results with no industry-specific semantic index or refined relevance.

xPatterns can build industry specific semantic index of all supplier web sites, technical data packages, NAICS codes and other related data (such as machines, materials, people, and certifications) to help analysts match prospective suppliers with RFPs and enhance procurement efficiency. xPatterns can:

  • Extend the analysts' ability to relate concepts together and assimilate critical data to match supplier capabilities to RFP requirements (parts, assemblies, equipment, manufacturing techniques, materials, skills, etc.)
  • Help direct contracts to more qualified businesses, thus increasing competition and making the supply chain more economical and responsive.
  • Track and account for events driving demand as well as other real-time data sources relevant to the procurement process.

Additionally, suppliers can leverage xPatterns to find government RFPs that match their exact capabilities:

RFP


Intelligence Analysis


The ability for analysts to rapidly identify, access, and analyze massive amounts of data potentially relevant to their agency is crucial. Traditional keyword search can limit the accuracy of results by surfacing only 20-30% of relevant matches. It is predominantly unreliable due to challenges in language variations (such as slang, misspellings, and encrypted messaging) which are highly prevalent across email, voice mail, SMS, and social media feeds.

With fast, dynamic software that goes beyond both keyword search and static ontology-based techniques, xPatterns finds the words we would not think of to describe the information we are looking for contained in: documents, news sources, social media feeds, etc. Based on these expanded search criteria, xPatterns reveals unforeseen connections between concepts that allow analysts to:

  • Navigate across huge disparate datasets by following links between related concepts
  • Connect related entities in real-time to support intelligence analysis
  • Increase efficiency in assimilating relevant data for intelligence