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Explore individual AI-powered workflow components that form the building blocks of custom workflows. Each component specializes in specific data processing tasks, from extraction to analysis to transformation.
Guide AI to analyze or extract information from your data using custom prompts.
Clean up a DataFrame by removing specified columns, columns with a high percentage of missing values, or rows with empty values in designated columns.
Computes a score for each data record based on a user-defined mathematical expression, enabling ranking and filtering.
Concatenates a list of columns into a new specified column.
Calculates the percentage distribution of distinct values within specified columns of a dataset.
Eliminates duplicate rows from the dataset to ensure data integrity and avoid redundant information.
Exports a structured dataset to a specified destination.
Extracts meaningful insights, such as sentiment, topics, and features.
Groups the dataset by a specified column and aggregates the values in the remaining columns.
Groups time series data based on a grouping column, a time column, and optional constraints on the maximum duration and maximum count within each group.
Converts JSON data to a structured dataset.
Limits the number of rows to process.
Creates or updates a column by evaluating a formula OR mapping numerical ranges.
Combines data from multiple sources into a unified dataset for analysis.
Rearranges the columns in a specific order to facilitate data exploration and analysis.
Groups similar text data points together based on their semantic or statistical similarity, revealing hidden patterns and insights.
Analyzes a text column by splitting values based on a specified delimiter and then counting the occurrences of each resulting item.
Splits values within a specified column based on a delimiter, creating a new row for each resulting value.