A network device (e.g., a user's mobile phone) may be used to make a telephone call to a landline telephone associated with a client device (e.g., a business's device). If the telephone call is terminated, either the network device or the client device may generate a text message to the other and establish a communication session. The client device may present a variety of options to the network device of service requests that may be completed by text message. The network device may transmit the service request and the service request may be fulfilled by the client.

A network device (e.g., a user's mobile phone) may be used to make a telephone call to a landline telephone associated with a client device (e.g., a business's device). If the telephone call is terminated, either the network device or the client device may generate a text message to the other and establish a communication session. The client device may present a variety of options to the network device of service requests that may be completed by text message. The network device may transmit the service request and the service request may be fulfilled by the client.

Implementations set forth herein relate to providing selectable autofill suggestions, which correspond to application actions that are at least partially fulfilled using server command data—prior to a user selecting a particular selectable autofill suggestion. Proactively fulfilling command data in this way mitigates latency between user selection of a suggestion and fulfillment of a particular action. Initially, a partial input can be processed to generate autofill suggestions, which can be communicated to a server device for further processing. The autofill suggestions can also be rendered for selection at a touch display interface, thereby allowing a user to select one of the autofill suggestions. As command fulfillment data is provided by the server, the command fulfillment data can be available to a corresponding application(s) in order that any corresponding actions can be at least partially fulfilled prior to user selection.

Implementations set forth herein relate to providing selectable autofill suggestions, which correspond to application actions that are at least partially fulfilled using server command data—prior to a user selecting a particular selectable autofill suggestion. Proactively fulfilling command data in this way mitigates latency between user selection of a suggestion and fulfillment of a particular action. Initially, a partial input can be processed to generate autofill suggestions, which can be communicated to a server device for further processing. The autofill suggestions can also be rendered for selection at a touch display interface, thereby allowing a user to select one of the autofill suggestions. As command fulfillment data is provided by the server, the command fulfillment data can be available to a corresponding application(s) in order that any corresponding actions can be at least partially fulfilled prior to user selection.

Users of a database management engine may generate fillable digital documents by mapping interface elements onto form documents. When a user maps interface elements onto a form document, the user may accidentally overlap two or more interface elements. To rectify this, the database management engine may modify the position of one of interface elements based on a set of positioning rules. In addition, the database management engine may identify and suggest mappings to users based on similar documents that have been previously mapped. The database management engine identifies similar documents using information about the document, the user, and the mapping itself. The mapping associated with the most similar document may be provided to the user as a suggested mapping. The database management engine converts the form document and finalized mapping into a fillable digital document. The fillable digital document is sent to recipients, who complete the fillable digital document.

Users of a database management engine may generate fillable digital documents by mapping interface elements onto form documents. When a user maps interface elements onto a form document, the user may accidentally overlap two or more interface elements. To rectify this, the database management engine may modify the position of one of interface elements based on a set of positioning rules. In addition, the database management engine may identify and suggest mappings to users based on similar documents that have been previously mapped. The database management engine identifies similar documents using information about the document, the user, and the mapping itself. The mapping associated with the most similar document may be provided to the user as a suggested mapping. The database management engine converts the form document and finalized mapping into a fillable digital document. The fillable digital document is sent to recipients, who complete the fillable digital document.

One embodiment provides a method, including: obtaining at least one video capturing images of a writing capture device used during a business process design session, wherein the images comprise portions of the process flow; obtaining at least one audio recording corresponding to the business process design session; identifying an intended business process model shape; determining at least one business process model shape missing from the process flow provided on the writing capture device; identifying a task dependency for pairs of business process model shapes; and generating a business process model from (i) the intended business process model shapes, (ii) the at least one business process model shape missing from the process flow, and (iii) the identified task dependencies.

One embodiment provides a method, including: obtaining at least one video capturing images of a writing capture device used during a business process design session, wherein the images comprise portions of the process flow; obtaining at least one audio recording corresponding to the business process design session; identifying an intended business process model shape; determining at least one business process model shape missing from the process flow provided on the writing capture device; identifying a task dependency for pairs of business process model shapes; and generating a business process model from (i) the intended business process model shapes, (ii) the at least one business process model shape missing from the process flow, and (iii) the identified task dependencies.

Disclosed herein are system, method, and computer program product embodiments for correcting extracted document information based on generated confidence and correctness scores. In an embodiment, a document correcting system may receive a document and document information that represents information extracted from the document. The document correcting system may determine the correctness of the document information by processing the document to generate a character grid representing textual information and spatial arrangements for the text within the document. The document correcting system may apply a convolutional neural network on character grid and the document information. The convolutional neural network may output corrected document information, a correctness value indicating the possible errors in the document information, and a confidence value indicating a likelihood of the possible errors.

Disclosed herein are system, method, and computer program product embodiments for correcting extracted document information based on generated confidence and correctness scores. In an embodiment, a document correcting system may receive a document and document information that represents information extracted from the document. The document correcting system may determine the correctness of the document information by processing the document to generate a character grid representing textual information and spatial arrangements for the text within the document. The document correcting system may apply a convolutional neural network on character grid and the document information. The convolutional neural network may output corrected document information, a correctness value indicating the possible errors in the document information, and a confidence value indicating a likelihood of the possible errors.