- 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
- Uploading a CSV file into a source
- Preparing data for .CSV upload
- 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
- Training chat and calls data
- 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
- Exchange Integration with Azure service user
- Exchange Integration with Azure Application Authentication
- Exchange Integration with Azure Application Authentication and Graph
- Fetching data for Tableau with Python
- Elasticsearch integration
- Self-hosted Exchange integration
- UiPath® Automation Framework
- UiPath® Marketplace activities
- 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
Understanding the data structure and permissions
- Data sources
- Datasets
- Projects
These are collections of raw, unannotated communications data of a similar type, such as all emails from a shared mailbox, or a collection of NPS survey responses. For more details, check Sources. You can associate individual data sources with up to 10 different datasets.
These are comprised of 1 to 20 data sources, of similar type with similar intended purposes, and the model that you create when you train the platform to understand the data in those sources. For more details, check Datasets.
Projects represent a permissioned storage area within the platform. Each dataset and data source belongs to a specific project, which is designated when they are created. For more details, check Projects.
Tenants allow you to model your organization structure, separating your business flows, and information similae to real-life organizations. Tenants are containers where you can organize your services and manage them for a group of users.
For example, you can create tenants for each of your departments and decide what services you want to enable for each, based on their needs. In each tenant, you can have one instance of each of the cloud services.
It is important to note that you cannot promote Communications Mining™ models between different UiPath® Cloud tenants. For example, promoting from Development to Production.
If you can only deploy to Production, in a Production environment, then enable the IXP service, which includes Communications Mining, in Production. However, if you have flexibility with deploying to Production, from another environment, you can have your Production automations call the platform from the tenant it sits in, for example, Quality Assurance or Development.
Permissions are per-user and specific to each project that a user belongs to. They can provide access to sensitive data and, depending on the permission, allow users to perform a range of different actions in the platform. For more details, check Roles and their underlying permissions.
If you are an Automation Cloud user, your IXP service, which includes Communications Mining, is enabled on a specific tenant. Tenants are where projects are stored.
Each dataset and data source is associated with a specific project, with users requiring permissions in those projects to be able to work with the data within them.
Datasets in one project can be made up of data sources from another project. Users require permissions in both projects to view and annotate the data.
The illustration depicts the relationship between these components and permissions:
- In the illustration, with Tenant A, all of the data sources are associated with Project A1, while there are datasets associated with both Project A1 and Project A2.
- If a user wanted to access datasets in Project A1, that is, dataset 1, 2, or 3, they would require viewing permissions for Project A1 only.
- However, if a user wanted to access datasets in Project A2, that is, dataset 4, 5, or 6, they would require viewing permissions for both Projects A1 and A2, because the data sources are all located in Project A1.
- To view project A1 or A2, the user would require access to Tenant A. To view project B1, the user would require access to Tenant B. The user permissions do not transfer cross-tenant.