Bring Sentiment Analysis
to Pydantic AI

Returns account-level metadata such as subscription tier, remaining processing credits, and user roles. Retrieve metadata and usage limits for your Deep Talk account

Resolves creation dates, source integrations, and whether NLP clustering has completed. Get metadata and processing status for a specific dataset

Returns a distribution of positive, neutral, and negative sentiment scores across the dataset records. Retrieve a summary of sentiment across the entire dataset

Returns dataset metadata including names, record counts, and current processing status for NLP analysis. List all conversation datasets uploaded for analysis

g., sentiment, intent, clusterers) that can be applied to datasets for analysis. List NLP models available for conversation categorization

Returns a list of connected external platforms, their synchronization status, and the volume of data ingested from each. List external data sources (e.g. Zendesk, Intercom) connected to Deep Talk

Returns groups of semantically similar conversations identified through unsupervised learning, including cluster sizes and representative keywords. List clusters of similar conversations identified in a dataset

Returns a list of identified themes with their respective prevalence and importance scores within the specified dataset. List key topics and themes extracted from the conversation data

Returns a list of active processing jobs, including ingestion and NLP analysis tasks, and their current completion percentages. List current data processing and analysis tasks

Identifies and returns themes that match the provided search term. Search for specific topics or themes within a dataset