Abstract: Embodiments of a method for facilitating spam blocking in a tiered software framework include: determining that a message template is generated in the tiered software framework, parsing the message template, automatically performing a semantic search for regulated content in the parsed message template, assigning a score to the message template based on the semantic search, and responsive to the score being higher than a predetermined threshold, blocking generating of any message from the message template. The tiered software framework comprises a first tier, a second tier, and a third tier, the second tier comprises accounts of a first plurality of subscribers, the third tier comprises subaccounts of the accounts, the subaccounts associated with a second plurality of subscribers, and the message template is associated with one of the subaccounts in the third tier.

Abstract: Embodiments of a method for facilitating business prospecting in a tiered software framework include receiving third-party data associated with prospects in a geographic location; analyzing the third-party data of each prospect against a plurality of criteria; reducing a portion of the analysis results to numerical values represented by icons; listing, in a first window of a user interface, the prospects in rows with corresponding icons in columns; and responsive to a selection of one of the rows, automatically opening a second window including another portion of the analysis results, the another portion including results from the analysis against the plurality of criteria.

Abstract: Embodiments of a method for automatically rebilling a metered activity comprise: detecting a metered activity in a tiered software framework having a first tier, a second tier, and a third tier with a first subscriber subscribed to the second tier, and a second subscriber subscribed to the third tier; instantiating a meter to monitor usage of the metered activity; simultaneously instantiating a first debit service at the first tier and a second debit service at the second tier; computing, by the first debit service, first usage credits of the usage; debiting the first usage credits from a first digital wallet of the first subscriber at the second tier; computing, by the second debit service, second usage credits of the usage; and debiting the second usage credits from a second digital wallet of the second subscriber at the third tier.

Abstract: Embodiments of a method for building funnel websites using artificial intelligence (AI) comprise providing a first tier, a second tier and a third tier, wherein: data in the first tier is accessible at the first tier and inaccessible at the second tier and the third tier, data in the second tier is accessible at the first tier and the second tier and inaccessible at the third tier, and data in the third tier is accessible at the first tier, the second tier and the third tier; providing, at the first tier, an AI engine; automatically generating, at the first tier using the AI engine, funnel website templates based on previously generated funnel websites; automatically building, at the first tier using the AI engine, a new funnel website using the funnel website templates for a subscriber to the third tier; and automatically deploying the new funnel website at the third tier.

Abstract: Disclosed herein are various embodiments for estimating shipping costs of items purchased on an online market. An embodiment operates by detecting a sales transaction between a seller and a buyer for an item via an online marketplace. An item vector representing the item as created by a deep learning model based on a plurality of characteristics associated with the item is received. A set of proximate vectors to the item vector, each of the proximate vectors corresponding to a past listings where a past shipping cost from shipping a product in the past listing is known are identified. A weighted average is calculated from the past shipping cost of each of the past listings. A dimensional weight of the item is estimated based on the weight average, and a shipping cost for the item is estimated based on the estimated dimensional weight prior to providing the item to a carrier.

Abstract: Provided herein are various embodiments of using machine readable technologies for the smart shipping of multiple products. An embodiment operates by receiving a request from a seller to ship a plurality of items that have been sold via an electronic marketplace. Information pertinent to shipping each of the plurality of items is predicted. A shipping company to ship the plurality of items is selected and provided the predicted information. A single machine readable code for shipping the plurality of items using the identified shipping company is determined based at least in part on the predicted information. A confirmation is received from the computing system of the shipping company responsive to the single machine readable code being scanned by a computing device of the computing system of the shipping company, the confirmation indicating that one or more of the plurality of items have been received by shipping company for shipment.

Abstract: Disclosed herein are various embodiments for estimating shipping costs of items purchased on an online market. An embodiment operates by detecting a sales transaction between a seller and a buyer for an item via an online marketplace. An item vector representing the item as created by a deep learning model based on a plurality of characteristics associated with the item is received. A set of proximate vectors to the item vector, each of the proximate vectors corresponding to a past listings where a past shipping cost from shipping a product in the past listing is known are identified. A weighted average is calculated from the past shipping cost of each of the past listings. A dimensional weight of the item is estimated based on the weight average, and a shipping cost for the item is estimated based on the estimated dimensional weight prior to providing the item to a carrier.

Abstract: Disclosed herein are system, method, and computer program product embodiments for estimating shipping costs of items purchased in an online market using machine learning techniques. By determining in real-time the dimensional weight of an item with reference to a machine learning model describing past transactions, a buyer and seller in the online market can finalize the transaction in real-time. The machine learning model further implements a bias within the machine learning algorithm towards heavier estimation to avoid undercharging the market participants for shipping costs. One embodiment involves using these cost-estimation techniques in the context of a local shipping feature, which allows buyers and sellers to schedule a same-day delivery by seamlessly involving a local carrier.

Abstract: Provided herein are various embodiments of using machine readable technologies for the smart shipping of multiple products. An embodiment operates by receiving a request from a seller to ship a plurality of items that have been sold via an electronic marketplace. Information pertinent to shipping each of the plurality of items is predicted. A shipping company to ship the plurality of items is selected and provided the predicted information. A single machine readable code for shipping the plurality of items using the identified shipping company is determined based at least in part on the predicted information. A confirmation is received from the computing system of the shipping company responsive to the single machine readable code being scanned by a computing device of the computing system of the shipping company, the confirmation indicating that one or more of the plurality of items have been received by shipping company for shipment.

Abstract: Provided herein are system, apparatus, article of manufacture, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for using innovative computer technologies to enable smart shipping of items sold from sellers to buyers. An embodiment performs operations that include: predicting shipping information for shipping an item associated with a first user to a destination designated by a second user, including determining a category of the item to identify similar items from a historical database; storing at least some of the shipping information in databases of an Internet site; and generating a machine readable code associated with the item or the shipping information, wherein a shipper uses information from scanning the code to access and retrieve the shipping information from the databases of the site using an application programming interface (API) of the site, and wherein the shipper uses the retrieved shipping information to ship the item to the destination.

Abstract: Disclosed herein are system, method, and computer program product embodiments for estimating shipping costs of items purchased in an online market using machine learning techniques. By determining in real-time the dimensional weight of an item with reference to a machine learning model describing past transactions, a buyer and seller in the online market can finalize the transaction in real-time. The machine learning model further implements a bias within the machine learning algorithm towards heavier estimation to avoid undercharging the market participants for shipping costs. One embodiment involves using these cost-estimation techniques in the context of a local shipping feature, which allows buyers and sellers to schedule a same-day delivery by seamlessly involving a local carrier.

Abstract: Provided herein are system, apparatus, article of manufacture, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for using innovative computer technologies to enable smart shipping of items sold from sellers to buyers. An embodiment performs operations that include: predicting shipping information for shipping an item associated with a first user to a destination designated by a second user, including determining a category of the item to identify similar items from a historical database; storing at least some of the shipping information in databases of an Internet site; and generating a machine readable code associated with the item or the shipping information, wherein a shipper uses information from scanning the code to access and retrieve the shipping information from the databases of the site using an application programming interface (API) of the site, and wherein the shipper uses the retrieved shipping information to ship the item to the destination.

Abstract: Audio level indicators are known which comprise moving needles, or an array of lights, or an illuminated bar. However, the way in which they provide information is fixed. A programmable audio level indicator for use with a mixing desk is provided which comprises a first light source arranged to emit a coloured light, in response to an audio signal received from a connected audio source, to indicate the audio level of that received signal, the indicator arranged to vary the colour and intensity of the light emitted as the audio level changes, wherein the indicator is configured such that the audio levels at which the colour changes are selectable, the indicator further configured such that the colour emitted to indicate an audio level, or range of audio levels, is also selectable.

Abstract: Audio level indicators are known which comprise moving needles, or an array of lights, or an illuminated bar. However, the way in which they provide information is fixed. A programmable audio level indicator for use with a mixing desk is provided which comprises a first light source arranged to emit a coloured light, in response to an audio signal received from a connected audio source, to indicate the audio level of that received signal, the indicator arranged to vary the colour and intensity of the light emitted as the audio level changes, wherein the indicator is configured such that the audio levels at which the colour changes are selectable, the indicator further configured such that the colour emitted to indicate an audio level, or range of audio levels, is also selectable.

Abstract: The present invention provides a class of pyrimidinedione cyclohexyl compounds and methods of using these compounds as glucocorticoid receptor modulators.