Abstract: Methods and systems provide for intelligent content recommendation within a communication session. In one embodiment, the system receives a list of content recommendation actions, each content recommendation action being associated with one or more trigger phrases constituting conditions for the content recommendation action to be performed, each trigger phrase being associated with a party the trigger phrase is to be uttered by. The system connects to a communication session with a plurality of participants, and receives a number of utterances associated with the participants in real time. For each utterance, the system determines whether a prediction of relatedness is present between the utterance and one or more trigger phrases associated with a content recommendation action. Upon determining that a prediction of relatedness is present, the system performs the associated content recommendation action by transmitting, to one or more client devices, one or more pieces of content to be recommended.

Abstract: Methods and systems provide for extracting next step sentences from a communication session. In one embodiment, the system defines a set of annotation guidelines for labeling training data; receives a set of labeled training data including sentences from a transcript of a communication session, a subset of the sentences being associated with a positive label; organizes the labeled training data and trains a model with the labeled training data, the training including, for each of the sentences, inputting the sentence into a language model and a classification head to output a number of class probabilities, and inputting a classification token representing the sentence into a classification head; using a number of classifiers from the trained model to generate ensemble class scores; and using the ensemble class scores to predict one or more next step sentences from the sentences in the transcript.

Abstract: Methods and systems provide for dynamically generated topic segments for a communication session. In one embodiment, the system connects to a communication session with a number of participants; receives a list of topics; receives a transcript of a conversation between the participants produced during the communication session, the transcript including timestamps for a number of utterances associated with speaking participants; for each topic in the list of topics, segments the utterances into one or more topic segments based on the topic; for each of the segments, classifies whether the topic segment is related to the topic, and transmits, to one or more client devices, a list of the topic segments for the communication session.

Abstract: Methods and systems provide for deal forecasting within a communication platform. In one embodiment, the system processes a communication session to provide analytics data for the session; receives internal data associated with a user of a communication platform pertaining to a deal, the internal data including internal analytics data for the deal derived from the communication session and one or more additional communication sessions; receives, from a CRM platform, updated CRM data pertaining to the deal; ingests the internal data and the updated CRM data into a standardized data repository; determines, via a model trained on the standardized internal data and updated CRM data, an outcome prediction for the deal; and provides, to one or more client devices, access to a presentation of the outcome prediction for the deal.

Abstract: Methods and systems provide for dynamic conversation alerts within a communication session. In one embodiment, the system presents, to a client device associated with a user of a communication platform, a user interface (“UP”) including a prompt for the user to submit one or more alert phrases, each alert phrase being associated with a category; receives, from the client device, a list of submitted alert phrases; and receives a transcript of a communication session between participants. For each utterance in the transcript, the system determines whether one or more predictions of relatedness are present between the utterance and one or more alert phrases from the list of submitted alert phrases. The system then transmits, to the client device, a list of related categories, each related category including one or more timestamps of utterances for which a prediction of relatedness is present for an alert phrase associated with that category.

Abstract: Methods and systems provide for dynamically generated topic segments for a communication session. In one embodiment, the system connects to a communication session with a number of participants; receives a list of topics; receives a transcript of a conversation between the participants produced during the communication session, the transcript including timestamps for a number of utterances associated with speaking participants; for each topic in the list of topics, segments the utterances into one or more topic segments based on the topic; for each of the segments, classifies whether the topic segment is related to the topic, and transmits, to one or more client devices, a list of the topic segments for the communication session.

Abstract: Methods and systems provide for dynamically generated topic segments for a communication session. In one embodiment, the system connects to a communication session with a number of participants; receives a list of topics; receives a transcript of a conversation between the participants produced during the communication session, the transcript including timestamps for a number of utterances associated with speaking participants; for each topic in the list of topics, segments the utterances into one or more topic segments based on the topic; for each of the segments, classifies whether the topic segment is related to the topic, and transmits, to one or more client devices, a list of the topic segments for the communication session.

Abstract: In one embodiment, the system connects to a communication session with a number of participants; receives a transcript of a conversation between the participants; extracts utterances from the transcript; associates a subset of the utterances with a first group of speakers and the remaining subset of the utterances with a second group of speakers; calculates one or more statistical metrics for a number of engagement metrics based on the utterances of the first group of speakers and the utterances of the second group of speakers; assigns a weight to each of the engagement metrics; determines an engagement score for the communication session based on the assigned weights for the engagement metrics; and presents, to one or more users, the engagement score for the communication session.

Abstract: Methods and systems provide an asynchronous pipeline for artificial intelligence service requests. In one embodiment, the system receives, at a gateway service, access to content associated with a communication session; sends, to an artificial intelligence (AI) cluster including a number of AI services, a data payload, the data payload including a location to access the content and a number of requests for AI services to be performed by one or more AI models hosted on the AI cluster using the content as an input; receives one or more AI service results as the AI cluster completes the corresponding requests for the AI services; and stores each received AI service result in one or more databases.