- Introduction
- Setting up your account
- Balance
- Clusters
- Concept drift
- Coverage
- Datasets
- General fields
- Labels (predictions, confidence levels, label hierarchy, and label sentiment)
- Models
- Streams
- Model Rating
- Projects
- Precision
- Recall
- Annotated and unannotated messages
- Extraction Fields
- Sources
- Taxonomies
- Training
- True and false positive and negative predictions
- Validation
- Messages
- Access control and administration
- Manage sources and datasets
- Understanding the data structure and permissions
- Creating or deleting a data source in the GUI
- Preparing data for .CSV upload
- Uploading a CSV file into a source
- Creating a dataset
- Multilingual sources and datasets
- Enabling sentiment on a dataset
- Amending dataset settings
- Deleting a message
- Deleting a dataset
- Exporting a dataset
- Using Exchange integrations
- Model training and maintenance
- Understanding labels, general fields, and metadata
- Label hierarchy and best practices
- Comparing analytics and automation use cases
- Turning your objectives into labels
- Overview of the model training process
- Generative Annotation
- Dastaset status
- Model training and annotating best practice
- Training with label sentiment analysis enabled
- Understanding data requirements
- Train
- Introduction to Refine
- Precision and recall explained
- Precision and Recall
- How validation works
- Understanding and improving model performance
- Reasons for label low average precision
- Training using Check label and Missed label
- Training using Teach label (Refine)
- Training using Search (Refine)
- Understanding and increasing coverage
- Improving Balance and using Rebalance
- When to stop training your model
- Using general fields
- Generative extraction
- Using analytics and monitoring
- Automations and Communications Mining™
- Developer
- Uploading data
- Downloading data
- Exchange Integration with Azure service user
- Exchange Integration with Azure Application Authentication
- Exchange Integration with Azure Application Authentication and Graph
- Migration Guide: Exchange Web Services (EWS) to Microsoft Graph API
- Fetching data for Tableau with Python
- Elasticsearch integration
- General field extraction
- Self-hosted Exchange integration
- UiPath® Automation Framework
- UiPath® official activities
- How machines learn to understand words: a guide to embeddings in NLP
- Prompt-based learning with Transformers
- Efficient Transformers II: knowledge distillation & fine-tuning
- Efficient Transformers I: attention mechanisms
- Deep hierarchical unsupervised intent modelling: getting value without training data
- Fixing annotating bias with Communications Mining™
- Active learning: better ML models in less time
- It's all in the numbers - assessing model performance with metrics
- Why model validation is important
- Comparing Communications Mining™ and Google AutoML for conversational data intelligence
- Licensing
- FAQs and more
Communications Mining user guide
Flex Plan
The licensing information on this page applies to you if you are on Flex. If you are on Unified Pricing, refer to the Communications Mining™ Unified Pricing.
Platform plans
The following table shows the features available in Communications Mining, within IXP, based on the Platform plan:
| Feature | Feature description | Basic Trial | Standard Trial | Enterprise Trial | Basic | Standard | Enterprise |
|---|---|---|---|---|---|---|---|
| Communications Data (Communications Mining™) | Access to Communications Mining capabilities, except for CMEK. | No | No | Yes | No | No | Yes |
| Customer Managed Encryption Key (CMEK) through multi-tenant and dedicated storage | Dedicated Communications Mining storage, or tenant for customer, that enables CMEK. Note: You must submit a request to enable this feature. For more details, contact your Sales representative. | No | No | By request | No | No | By request |
*The Basic+ plan enhances the Basic plan by including additional features.
Metering and charging logic (Flex)
Measuring consumption
Communications Mining™ utilization is measured based on the consumption rate of units.
Consuming units
In Communications Mining, units are consumed when data is uploaded to the platform, at a rate of 1 AI Unit per upload, as follows:
- Per created message, for example, a comment in the API, such as an email.
- Per updated message, if the text of the data was modified.
Note:
As Communications Mining models continuously retrain, and predictions automatically update, you are not charged on a per-prediction basis, but per message.
You will be charged 1 AI Unit per message for the following operations:
- Uploading data into the platform via the API.
- Uploading comments or raw emails (sync and sync-raw-email routes).
- Fetching predictions for comments or raw emails that are not in the platform (predict and predict-raw-email routes).
- Uploading data into the platform via the CLI.
- Uploading data into the platform via integrations.
- Syncing emails via the Exchange Integration
- Syncing Salesforce objects via the Salesforce Integration
- Uploading data into the platform via the platform user interface.
Once uploaded, Communications Mining stores messages with no additional charge for 2 years.
AI Units consumption
This section outlines how metering and charging for AI Units are determined based on the type of operation you perform:
| Product | Capability | Charge details | Activity or model | AI Units consumed |
|---|---|---|---|---|
| Intelligent Extraction (IXP) | Communications Data (Communications Mining™) | Per Message uploaded, modified, or predicted | Classification and extraction | 1 |