Abstract: An artificial intelligence enhanced method for optimizing operational deployment of field resources using network Voronoi Tessellations in combination with the aggregation and consideration of numerous data elements. Resources deployed in the field utilize modes of transportation that are represented by a network topology, which can be influenced by external sources of information that pertain to nodes in the network or nodes in other network topologies, which can be used by an artificial intelligence processor to develop optimized routes for deployed field resources in a continuous manner. The incorporation of these sources of information that can influence the topology of the network is utilized to determine the optimal deployment of field resources.

Abstract: An artificial intelligence enhanced method for optimizing operational deployment of field resources using network Voronoi Tessellations in combination with the aggregation and consideration of numerous data elements. Resources deployed in the field utilize modes of transportation that are represented by a network topology, which can be influenced by external sources of information that pertain to nodes in the network or nodes in other network topologies, which can be used by an artificial intelligence processor to develop optimized routes for deployed field resources in a continuous manner. The incorporation of these sources of information that can influence the topology of the network is utilized to determine the optimal deployment of field resources.

Abstract: A vendor matching engine and method of use, which may be used by a prospective bidder on a government contract or another prospective selectee in order to determine which bids or applications are most worthwhile to pursue. The engine may perform steps of retrieving transactional or vendor registry information, such as Federal Procurement Data System data or System for Award Management data, and may then use this data to generate matchability scores characterizing the compatibility between the selector and selectee. To generate these scores, the distances between selector and selectee coordinates in n-dimensional space may be used in order to determine how similar the prospective selectee is to the selector's desired selectee, allowing a vendor to prioritize government contracts for which they may be best suited. The system may also be used for other pairings of applicants and awarding parties, such as universities and research granting organizations.

Abstract: A vendor matching engine and method of use, which may be used by a prospective bidder on a government contract or another prospective selectee in order to determine which bids or applications are most worthwhile to pursue. The engine may perform steps of retrieving transactional or vendor registry information, such as Federal Procurement Data System data or System for Award Management data, and may then use this data to generate matchability scores characterizing the compatibility between the selector and selectee. To generate these scores, the distances between selector and selectee coordinates in n-dimensional space may be used in order to determine how similar the prospective selectee is to the selector's desired selectee, allowing a vendor to prioritize government contracts for which they may be best suited. The system may also be used for other pairings of applicants and awarding parties, such as universities and research granting organizations.