A system and method for rules-driven adjudication is disclosed. The system includes a storage includes a rule library having a plurality of rules, each rule being in a human-readable format and including a first data tag, a comparator, a comparison value, and a result. The system also includes a rules manager configured to receive and store a new rule. The system includes a rules evaluator configured to receive an adjudication request having a data object associated with a data tag, and evaluate the request and create a primary determination by applying a first rule to the request, and further applying a first subsequent rule and all logically adjacent rules until all logically adjacent rules have been exhausted and the primary determination is an indefinite outcome or the applying of a final rule returns an outcome that becomes the primary determination.

Example implementations include a system to generate a user object, with a data processing system comprising memory and one or more processors to identify a role attribute of a user object, a geography attribute of the user object, and a temporal attribute of the user object, determine, based on the role attribute, the geography attribute, and the temporal attribute, a benefits group corresponding to the user object, generate a dynamic association of the user object to the benefits group, the dynamic association from the role attribute, the geography attribute, and the temporal attribute, and modifiable in response to a modification of one or more of the role attribute, the geography attribute, and the temporal attribute, and generate a dynamic tree structure from the dynamic association, the tree structure modifiable in response to the modification of one or more of the role attribute, the geography attribute, and the temporal attribute.

The computerized staffing platform includes a staffing server with a processor configured to store data indicating available shifts from third-party businesses and data indicating employees of the platform registered to fulfill the available shifts. The processor is configured to receive a request from a particular business to fulfill a target available shift, and determine candidate employees to fulfill the target available shift. The processor is configured to compute a predicted labor burden associated with hiring each candidate employee for the target available shift, including whether the candidate employee has exceeded an income threshold after which a labor burden factor no longer applies. The processor is further configured to send, to the particular business, a list of the candidate employees and the predicted labor burden for each candidate employee, receive a selection of a candidate employee, and send, to the selected candidate employee, an offer to fulfill the available target shift.

Aspects extract, from payroll data of employees of an organization, data historically associated to previous instances of certified tax credit eligibility; normalize the extracted data with respect to data type and data value; generate from the normalized extracted data via a neural network classifier multi-class outputs for each employee that indicate strengths of likelihood that each employee is currently eligible for each of a plurality of different tax credits; filter the normalized extracted data by removing portions associated to employees indicated within the multi-class outputs as having no currently eligible likelihood for the different tax credits, thereby generating a remainder set of normalized extracted data associated to remainder eligible ones of the employees; and prioritize application for the tax credits for the remainder eligible employees as a function of respective values and likelihoods of eligibility within the remainder set of normalized extracted data.

Aspects extract, from payroll data of employees of an organization, data historically associated to previous instances of certified tax credit eligibility; normalize the extracted data with respect to data type and data value; generate from the normalized extracted data via a neural network classifier multi-class outputs for each employee that indicate strengths of likelihood that each employee is currently eligible for each of a plurality of different tax credits; filter the normalized extracted data by removing portions associated to employees indicated within the multi-class outputs as having no currently eligible likelihood for the different tax credits, thereby generating a remainder set of normalized extracted data associated to remainder eligible ones of the employees; and prioritize application for the tax credits for the remainder eligible employees as a function of respective values and likelihoods of eligibility within the remainder set of normalized extracted data.

A central database system receives information associated with an employee from an employer. Using this information, the central database system can provision one or more user accounts for the employee, for instance via an API of an account provider. The central database system can use a machine learned model to identify fields of the API and to translate the information associated with the employee based on information requirements associated with the API. When a characteristic of the employee, such as the employee's title, subsequently changes within the central database system, one or more features associated with the user account can be automatically updated in response to the change.

A central database system receives information associated with an employee from an employer. Using this information, the central database system can provision one or more user accounts for the employee, for instance via an API of an account provider. The central database system can use a machine learned model to identify fields of the API and to translate the information associated with the employee based on information requirements associated with the API. When a characteristic of the employee, such as the employee's title, subsequently changes within the central database system, one or more features associated with the user account can be automatically updated in response to the change.

One or more embodiments describe techniques for proactively connecting members of an organization together based on detected interest in a particular topic. The system analyzes a profile of a member to detect a particular topic associated with the member, and based on evaluating a set of interactions that another member of the organization had regarding the particular topic, generates an overall connection score for rating a connection between the second member and the particular topic. Responsive to determining that the overall connection score meets a threshold value, the system transmits a communication to generate a connection between the two members, and any other members whose overall connection scores meet the threshold value, for initiating collaboration on the particular topic amongst the various connected members.

One or more embodiments describe techniques for proactively connecting members of an organization together based on detected interest in a particular topic. The system analyzes a profile of a member to detect a particular topic associated with the member, and based on evaluating a set of interactions that another member of the organization had regarding the particular topic, generates an overall connection score for rating a connection between the second member and the particular topic. Responsive to determining that the overall connection score meets a threshold value, the system transmits a communication to generate a connection between the two members, and any other members whose overall connection scores meet the threshold value, for initiating collaboration on the particular topic amongst the various connected members.

A digital mailroom application is used by a mail clerk to process incoming physical mail. The digital mailroom application receives a list of mail recipients and mail delivery settings, then processes the incoming physical mail using the list of mail recipients and mail delivery settings. A piece of incoming physical mail can be processed by determining one of the mail recipients as the recipient for the piece of physical mail. The piece of physical mail is then scanned to generate a corresponding digital mail piece, which is routed electronically based on the defined mail delivery settings.