Abstract: Apparatuses, systems and methods are disclosed for providing property improvement recommendations. The method comprises: (1) receiving, by one or more processors from a user, a first prompt associated with a property; (2) generating, by the one or more processors, a second prompt based upon the first prompt, data associated with the property and one or more property metrics associated with the property; (3) transmitting, by the one or more processors to a chatbot, the second prompt to generate a response, the response comprising a recommended action associated with the property; and/or (4) presenting, by the one or more processors, the response to the user.

Abstract: Systems and methods disclosed herein relate to fine-tuning machine learning (ML) chatbots for an enterprise. The systems and methods may use ML chatbots and/or generative ML to generate social media content for a user associated with an enterprise. The systems and methods may fine-tune a base ML model, and use the fine-tuned ML model for the ML chatbot. A user profile may indicate user attributes, and a fine-tuned ML model may be loaded for the ML chatbot based upon an identified user profile.

Abstract: Apparatuses, systems and methods are disclosed for providing customer-specific information. The method comprises: (1) receiving, by one or more processors from a user device, a first prompt associated with a customer; (2) creating, by the one or more processors, a vector associated with the first prompt; (3) comparing, by the one or more processors, the vector associated with the first prompt with vectors associated with a plurality of documents associated with the customer to identify one or more candidate documents from the plurality of documents; (4) creating, by the one or more processors, a second prompt based upon the first prompt and the one or more candidate documents; (5) inputting, by the one or more processors, the second prompt into a chatbot to obtain a response to the second prompt; and/or (6) presenting, by the one or more processors, the response via the user device.

Abstract: Apparatuses, systems, and methods are provided for career development are provided. The method comprises: (1) receiving, by one or more processors from a user device, an information element associated with a user; (2) generating, by the one or more processors via a chatbot, career development suggestions based upon the information element associated with the user; and/or (3) presenting, by the one or more processors to the user via the user device, the career development suggestions. The chatbot may implement a trained model.

Abstract: Apparatuses, systems, and methods are provided for training employees are provided. The method comprises: (1) receiving, by one or more processors from a user device associated with an employee, an answer associated with a question; (2) generating, by the one or more processors via a chatbot, values associated with one or more metrics of the answer; and/or (3) performing, by the one or more processors, at least one of the following: (i) determining a skill level of the employee based upon the values associated with the one or more metrics of the answer; (ii) presenting, to the employee via the user device, a second question based upon the values associated with the one or more metrics of the answer; and/or (iii) presenting, to the employee via the user device, an explanation based upon the values associated with the one or more metrics of the answer.

Abstract: Systems and methods disclosed herein relate to fine-tuning machine learning (ML) chatbots for an enterprise. The systems and methods may use ML chatbots and/or generative ML to provide information to a user in a manner emulating the traits of a person. The systems and methods may fine-tune a base ML model, and use the fine-tuned ML model for the ML chatbot. The user may indicate a person associated with the fine-tuned ML model, and the fine-tuned ML model associated with the person may be loaded for the ML chatbot.

Abstract: Systems and methods disclosed herein relate to fine-tuning machine learning (ML) chatbots for an enterprise. The systems and methods may use ML chatbots and/or generative ML to provide information to a user based upon the user's interaction at a portal of an enterprise. The systems and methods may fine-tune a base ML model, and use the fine-tuned ML model for the ML chatbot. The user's interactions may be classified as a type of user activity. A fine-tuned ML model may be loaded as the ML chatbot based upon the type of user activity.

Abstract: Blockchain-based systems and methods for managing digital currency associated with a company or organization are disclosed. The digital currency may be used to reward or incentivize behaviors of employees, clients, and/or prospective clients or customers of a company, organization, or other entity. A blockchain computing device in accordance with the present disclosure may include at least one memory and at least one processor in communication with the at least one memory. The processor may be programmed to, in response to a predetermined criterion being met, automatically generate a reward token transaction, broadcast the reward token transaction to a blockchain network, validate the reward token transaction, and generate and store a new block on the blockchain network with the reward token transaction.

Abstract: Techniques are described herein for marking virtual objects. An exemplary system includes one or more processors; and a non-transitory computer-readable medium coupled to the one or more processors and storing instructions thereon. The instructions, when executed by the one or more processors, cause the one or more processors to: (1) receive a transaction listing from a first entity, the transaction listing including (i) a digital asset that is associated with a virtual object in a virtual environment and (ii) a status of the digital asset indicating an active association with the first entity, (2) generate a transaction based upon the transaction listing, the transaction including an indication of the virtual object, (3) record the transaction in a distributed ledger, and (4) responsive to recording the transaction in the distributed ledger, cause the status of the digital asset to be displayed when the virtual object is viewed in the virtual environment.

Abstract: Techniques are described herein for minting digital assets associated with user achievements in a distributed network. An exemplary system includes one or more processors; and a non-transitory computer-readable medium coupled to the one or more processors and storing instructions thereon. The instructions, when executed by the one or more processors, cause the one or more processors to: (1) receive an update from a platform application on a user computing device, the update including (i) an association indication between a first entity of the user computing device and a second entity and (ii) an achievement of the first entity; (2) generate a transaction based upon the update, the transaction including a digital asset associated with the update; (3) record the transaction in a distributed ledger; and (4) responsive to recording the transaction in the distributed ledger, transmit a notification to the user computing device indicating the digital asset.

Abstract: Techniques are described herein for managing transactions associated with vehicles using a distributed ledger maintained by a plurality of participants. An exemplary system includes one or more processors; and a non-transitory computer-readable medium coupled to the one or more processors and storing instructions thereon. The instructions, when executed by the one or more processors, cause the one or more processors to: (1) receive a transaction listing from a first entity, the transaction listing including (i) entity data corresponding to the first entity, (ii) a non-fungible token (NFT) corresponding to a vehicle, and (iii) an updated state of the vehicle; (2) generate a transaction including a description of the transaction listing; and (3) record the transaction in a distributed ledger. A vehicle identification number (VIN) of the vehicle may be linked to the NFT in the distributed ledger.

Abstract: Systems and methods are disclosed for generating one or more smart contracts for deployment onto a blockchain. The systems and methods may include (1) receiving vehicle information related to a vehicle; (2) analyzing the vehicle information to identify one or more safety features installed in the vehicle; (3) generating, based upon the one or more safety features identified, a smart contract that may be configured to (i) maintain a set of indications related to whether safety features in the one or more safety features installed in the vehicle have been activated, and (ii) automatically execute on the blockchain based upon the maintained set of indications; and/or (4) deploying the smart contract at a particular address on the blockchain.

Abstract: Systems and methods are disclosed for generating one or more smart contracts for deployment onto a blockchain. The systems and methods may include (1) receiving vehicle information related to a vehicle; (2) analyzing the vehicle information to identify one or more safety features installed in the vehicle; (3) generating, based upon the one or more safety features identified, a smart contract that may be configured to (i) maintain a set of indications related to whether safety features in the one or more safety features installed in the vehicle have been activated, and (ii) automatically execute on the blockchain based upon the maintained set of indications; and/or (4) deploying the smart contract at a particular address on the blockchain.

Abstract: Systems and methods are disclosed for generating one or more smart contracts for deployment onto a blockchain. The systems and methods may include (1) receiving vehicle information related to a vehicle; (2) analyzing the vehicle information to identify one or more safety features installed in the vehicle; (3) generating, based upon the one or more safety features identified, a smart contract that may be configured to (i) maintain a set of indications related to whether safety features in the one or more safety features installed in the vehicle have been activated, and (ii) automatically execute on the blockchain based upon the maintained set of indications; and/or (4) deploying the smart contract at a particular address on the blockchain.

Abstract: Systems and methods are disclosed for generating one or more smart contracts for deployment onto a blockchain. The systems and methods may include (1) receiving vehicle information related to a vehicle; (2) analyzing the vehicle information to identify one or more safety features installed in the vehicle; (3) generating, based upon the one or more safety features identified, a smart contract that may be configured to (i) maintain a set of indications related to whether safety features in the one or more safety features installed in the vehicle have been activated, and (ii) automatically execute on the blockchain based upon the maintained set of indications; and/or (4) deploying the smart contract at a particular address on the blockchain.

Abstract: Systems and methods are disclosed for generating one or more smart contracts for deployment onto a blockchain. The systems and methods may include (1) receiving vehicle sensor data generated from sensors mounted on or within (a) one or more vehicles, or (b) electronic devices; (2) analyzing the vehicle sensor data to determine one or more parametric events, wherein each of the parametric events is associated with a corresponding severity of loss; (3) generating, for each of the one or more parametric events, a corresponding smart contract that is configured to (i) receive a transaction from a computing device, and (ii) automatically execute on the blockchain when the transaction indicates that a parametric event corresponding to the smart contract has occurred; and (4) deploying the smart contract at a particular address on the blockchain.

Abstract: Systems and methods are disclosed for generating one or more smart contracts for deployment onto a blockchain. The systems and methods may include (1) receiving vehicle sensor data generated from sensors mounted on or within (a) one or more vehicles, or (b) electronic devices; (2) analyzing the vehicle sensor data to determine one or more parametric events, wherein each of the parametric events is associated with a corresponding severity of loss; (3) generating, for each of the one or more parametric events, a corresponding smart contract that is configured to (i) receive a transaction from a computing device, and (ii) automatically execute on the blockchain when the transaction indicates that a parametric event corresponding to the smart contract has occurred; and (4) deploying the smart contract at a particular address on the blockchain.

Abstract: Systems and methods are disclosed for providing a graphic user interface. The systems and methods may (1) receive an indication of a parametric event involving a vehicle; (2) provide a series of component graphic user interfaces, wherein the component graphic user interfaces may be configured to (i) initiate a claim filing, (ii) communicate with an insurer entity, (iii) communicate with an emergency response entity, (iv) communicate with a towing service entity, (v) communicate with a taxi or ride-share service entity, (vi) communicating with a vehicle repair service entity, (vii) communicating with a vehicle salvage entity, and/or (viii) communicating with a vehicle rental service entity; (3) detect one or more user interactions that may include one or more selections of the one or more actions; (4) perform the one or more actions; and/or (5) record a transaction indicating that the one or more actions has been performed to the blockchain.

Abstract: Systems and methods are disclosed for generating one or more smart contracts for deployment onto a blockchain. The systems and methods may include (1) receiving vehicle sensor data generated from sensors mounted on or within (a) one or more vehicles, or (b) electronic devices; (2) analyzing the vehicle sensor data to determine one or more parametric events, wherein each of the parametric events is associated with a corresponding severity of loss; (3) generating, for each of the one or more parametric events, a corresponding smart contract that is configured to (i) receive a transaction from a computing device, and (ii) automatically execute on the blockchain when the transaction indicates that a parametric event corresponding to the smart contract has occurred; and (4) deploying the smart contract at a particular address on the blockchain.

Abstract: Systems and methods are disclosed for generating one or more smart contracts for deployment onto a blockchain. The systems and methods may include (1) receiving vehicle sensor data generated from sensors mounted on or within (a) one or more vehicles, or (b) electronic devices; (2) analyzing the vehicle sensor data to determine one or more parametric events, wherein each of the parametric events is associated with a corresponding severity of loss; (3) generating, for each of the one or more parametric events, a corresponding smart contract that is configured to (i) receive a transaction from a computing device, and (ii) automatically execute on the blockchain when the transaction indicates that a parametric event corresponding to the smart contract has occurred; and (4) deploying the smart contract at a particular address on the blockchain.