Abstract: Customer relationship management (“CRM”) implemented in a computer system, including parsing, by a parsing engine of the computer system into parsed triples of a description logic, words of a CRM event from an incoming stream of CRM events, the CRM event characterized by an event type, the stream implemented in a CRM application of the computer system; and inferring, by an inference engine from the parsed triples according to inference rules specific to the event type, inferred triples.

Abstract: A system for electronic lead generation including a semantic graph database including a knowledge graph and a dynamic profiling module comprising automated computing machinery configured to identify a near-term surge in product interest for a number of companies of a particular size in a particular industry in a particular region of the world in dependence upon the knowledge graph and create a company profile in dependence upon the size of the identified companies, the industry of the identified companies, and the region of the world of the identified companies associated with the near-term surge. Embodiments also include a lead purchase module comprising automated computing machinery configured to generate an electronic lead purchase order in dependence upon the company profile; transmit the lead purchase order to a lead generation engine; and receive, from the lead generation engine, a plurality of leads in dependence upon the lead purchase order.

Abstract: Embodiments of the present invention include a dynamic script engine for tele-agents including a statistics engine configured to receive, during a sales call, real-time industry trend data from one or more remote industry resources; create a current industry score in dependence upon the industry trend data and current products available to a customer on an active call; and transmit the current industry score to a script generator; and a script generator configured to receive the current industry score from the statistics engine and dynamically reorder in real-time and in dependence upon the industry score one or more sentences of a dynamic script to be read by a sales agent to the customer during the sales call.

Abstract: Customer relationship management (“CRM”) implemented in a computer system, including parsing a word, from call notes of a conversation between a tele-agent of a call center and a customer representative, into a parsed triple of a description logic; determining whether the parsed triple is recorded in a semantic CRM triple store of the computer system; if the parsed triple is not recorded in the semantic CRM triple store, recording the parsed triple as a call note in the semantic CRM triple store.

Abstract: Customer relationship management (“CRM”) implemented in a computer system, including establishing by the computer system, upon a first communications contact between a tele-agent and a customer representative, as structure of computer memory of the computer system, a communications session; and administering by the computer system through the communications session across communications platforms a sequence of communications contacts, including the first contact and also subsequent communications contacts, between the tele-agent and the customer representative.

Abstract: Customer relationship management (‘CRM’) implemented in a computer system, including administering, by an artificial intelligence agent (‘AIA’) of a CRM application of the computer system, with a customer representative on behalf of a tele-agent, as structure of computer memory of the computer system, a communications session comprising one or more communications contacts with the customer representative; and effecting by the AIA communications with the tele-agent in support of the communications session.

Abstract: Configuring computer memory including parsing digitized speech into a triples of a description logic; determining whether parsed triples are recorded in a general language triple store of the computer memory; determining whether parsed triples are recorded in a jargon triple store of the computer memory; and, if the parsed triples are recorded in neither the general language triple store nor the jargon triple store, recording the parsed triples in the jargon triple store.

Abstract: Customer relationship management (‘CRM’) implemented in a computer system, including administering, by an artificial intelligence agent (‘AIA’) of a CRM application of the computer system, with a customer representative on behalf of a tele-agent, as structure of computer memory of the computer system, a communications session comprising one or more communications contacts with the customer representative; and effecting by the AIA communications with the tele-agent in support of the communications session.

Abstract: Customer relationship management (‘CRM’) implemented in a computer system, including administering, by an artificial intelligence agent (‘AIA’) of a CRM application of the computer system, with a customer representative on behalf of a tele-agent, as structure of computer memory of the computer system, a communications session comprising one or more communications contacts with the customer representative; and effecting by the AIA communications with the tele-agent in support of the communications session.

Abstract: Customer relationship management (‘CRM’) implemented in a computer system, including administering, by an artificial intelligence agent (‘AIA’) of a CRM application of the computer system, with a customer representative on behalf of a tele-agent, as structure of computer memory of the computer system, a communications session comprising one or more communications contacts with the customer representative; and effecting by the AIA communications with the tele-agent in support of the communications session.

Abstract: Customer relationship management (“CRM”) implemented in a computer system, including establishing by the computer system, upon a first communications contact between a tele-agent and a customer representative, as structure of computer memory of the computer system, a communications session; and administering by the computer system through the communications session across communications platforms a sequence of communications contacts, including the first contact and also subsequent communications contacts, between the tele-agent and the customer representative.

Abstract: Customer relationship management (“CRM”) implemented in a computer system, including parsing, by a parsing engine of the computer system into parsed triples of a description logic, words of a CRM event from an incoming stream of CRM events, the CRM event characterized by an event type, the stream implemented in a CRM application of the computer system; and inferring, by an inference engine from the parsed triples according to inference rules specific to the event type, inferred triples.

Abstract: Configuring computer memory including parsing digitized speech into a triples of a description logic; determining whether parsed triples are recorded in a general language triple store of the computer memory; determining whether parsed triples are recorded in a jargon triple store of the computer memory; and, if the parsed triples are recorded in neither the general language triple store nor the jargon triple store, recording the parsed triples in the jargon triple store.

Abstract: Customer relationship management (‘CRM’) implemented in a computer system, including administering by the computer system a communications session that includes a sequence of communications contacts between a tele-agent and one or more customer representatives, the session and each contact composed of structured computer memory of the computer system; and generating by the computer system a digital transcript of the content of the communications contacts.

Abstract: Customer relationship management (“CRM”) implemented in a computer system, including parsing a word, from call notes of a conversation between a tele-agent of a call center and a customer representative, into a parsed triple of a description logic; determining whether the parsed triple is recorded in a semantic CRM triple store of the computer system; if the parsed triple is not recorded in the semantic CRM triple store, recording the parsed triple as a call note in the semantic CRM triple store.

Abstract: A system for electronic lead generation including a semantic graph database including a knowledge graph and a dynamic profiling module comprising automated computing machinery configured to identify a near-term surge in product interest for a number of companies of a particular size in a particular industry in a particular region of the world in dependence upon the knowledge graph and create a company profile in dependence upon the size of the identified companies, the industry of the identified companies, and the region of the world of the identified companies associated with the near-term surge. Embodiments also include a lead purchase module comprising automated computing machinery configured to generate an electronic lead purchase order in dependence upon the company profile; transmit the lead purchase order to a lead generation engine; and receive, from the lead generation engine, a plurality of leads in dependence upon the lead purchase order.

Abstract: Embodiments of the present invention include a dynamic script engine for tele-agents including a statistics engine configured to receive, during a sales call, real-time industry trend data from one or more remote industry resources; create a current industry score in dependence upon the industry trend data and current products available to a customer on an active call; and transmit the current industry score to a script generator; and a script generator configured to receive the current industry score from the statistics engine and dynamically reorder in real-time and in dependence upon the industry score one or more sentences of a dynamic script to be read by a sales agent to the customer during the sales call.

Abstract: Systems and methods are provided for assessing a risk associated with a requirements document and/or identifying one or more resources that can be used to manage the risk. A requirements document can be analyzed to extract elements from the requirements document into relationships. A relationship interface can be generated that includes the relationships for the requirements document. Information, associated with an entity or otherwise, relevant to the requirements document can be organized into risk issues using the relationships interface. One or more resources may be identified for the information relevant to the requirements document and an interface can be provided between the identified resource and a manager of the requirements document.