Intuit Inc.

Performing web application based screen share annotations includes obtaining, from a source browser executing a web application performing a screen sharing, a location point of the source browser with respect to a shared source screen being shared. Performing web application based screen share annotations further includes calculating, from the location point, a source portion of the shared source screen that shows the web application, translating the source portion to a target portion within a target web browser executing on a target device. Performing web application based screen share annotations further includes demarcating, on the target display, the target portion within the target browser.

At least one processor may receive a user prompt from a user and determine a user role associated with the user. The at least one processor may select a system prompt associated with the user role and identify at least one data source from among a plurality of available system prompts each associated with a different respective user role and indicating one or more data sources accessible according to the respective user role. The at least one processor may build a final prompt configured to retrieve data responsive to the user prompt from the at least one data source. The at least one processor may query a generative artificial intelligence (GenAl) system using the final prompt, the querying causing the GenAl system to access the at least one data source identified by the system prompt and provide a response incorporating data obtained from the at least one data source.

Aspects of the present disclosure relate to techniques for deriving cryptographic keys. Embodiments include using a key encapsulation mechanism to encrypt various data items transferred between a first remote server and a client device during a key derivation process. In some embodiments, the encrypted data items include a blinding value and a client key. Embodiments further include using a hybrid post-quantum key exchange technique to securely store and transfer keys used by the remote servers as part of the key derivation process.

Certain aspects of the disclosure provide systems and methods for field narration. For example, field narration may be configured to populate and verify a form populated based on audio data. A user interface may send a verification request for the form, including a data field and a value to be verified to a field narrative service. The field narrative service may determine relevant portions of the audio data and the transcript for the value to be verified. The user interface may play the portion of audio data, and display the transcription for verification.

Aspects of the present disclosure relate to automated content modality transformation. Embodiments include receiving content that corresponds to a particular modality. Embodiments further include providing the content as input to a generative machine learning model that has been trained to generate versions of provided content items that correspond to a target modality. Embodiments further include receiving, as an output from the generative machine learning model, a new version of the content that corresponds to the target modality. Embodiments further include providing the content and the new version of the content as input to a given machine learning model that is trained to generate a confidence score that indicates a likelihood that the new version is an accurate representation of the content in the target modality. Embodiments further include performing one or more actions involving the new version of the content based on the confidence score.

A method includes obtaining an expert availability forecasting model including at least a first time slot, a multitude of available experts corresponding to the at least first time slot, and a predicted customer demand corresponding to the at least first time slot. An expert allocation model is generated, including a first set of available experts allocated to the at least first time slot based on the expert availability forecasting model. A first set of customers is selected, corresponding to the predicted customer demand. The first set of customers is matched to the corresponding first set of available experts in the at least first time slot, based on the expert allocation model, to obtain a customer-expert allocation schedule. The method further includes transmitting the customer-expert allocation schedule to a performance analytics dashboard. The method further includes monitoring at least one data source for at least one expert availability event.

Aspects of the present disclosure relate to automated analytical content generation. Embodiments include receiving data from one or more data sources. Embodiments further include extracting trends from the data using a heuristic algorithm. Embodiments further include providing an input based on the extracted trends to a generative machine learning model that has been configured to generate content based on extracted trends. Embodiments further include receiving, from the generative machine learning model based on the input, content that represents the extracted trends. Embodiments further include displaying the content via a user interface.

Aspects of the present disclosure relate to automated document integration. Embodiments include receiving one or more documents from a user. Embodiments further include extracting, using a computer vision machine learning model, a first data item from the one or more documents. Embodiments further include generating a prompt based on a second data item not being present in the one or more documents, wherein the prompt comprises a request for the user to provide the second data item. Embodiments further include receiving, based on the prompt, an additional document from the user. Embodiments further extracting, using the computer vision machine learning model, the second data item from the additional document. Embodiments further include generating, via a particular machine learning model based on the first data item and the second data item, an electronic document that corresponds to a particular format.

Certain aspects of the disclosure provide systems and methods for audio-based form population and verification. Aspects include requesting and receiving a transcript of audio data associated with a form with a data field and a value associated with the data field, from a speech recognition model, wherein the transcript comprises the words spoken in the audio data; and a pair of timestamps associated with each word spoken in the audio data. Then, the data field is mapped to one or more words spoken in the audio data and used to populate the data field with the value.

Certain aspects of the disclosure provide a method for fraud detection. The method may include obtaining a plurality of fraud detection rule combinations, each fraud detection rule combination of the plurality of fraud detection rule combinations having an assigned risk level, wherein each fraud detection rule combination comprises a combination of two or more individual fraud detection rules; receiving transaction data associated with an account; identifying, from the plurality of fraud detection rule combinations, one or more fraud detection rule combinations triggered by the transaction data, and generating a consolidated risk score for the account by aggregating the assigned risk levels of each triggered fraud detection rule combination; and generating a fraud alert when the consolidated risk score exceeds a threshold, wherein the fraud alert includes an explanation identifying the one or more fraud detection rule combinations that contributed to the consolidated risk score.