- Release Notes
- Getting started
- Notifications
- Projects
- Datasets
- Data Labeling
- ML packages
- Out of the box packages
- Pipelines
- ML Skills
- ML Logs
- Document UnderstandingTM in AI Center
- AI Center API
- Licensing
- AI Solutions Templates
- How to
- Basic Troubleshooting Guide

AI Center
Platform Units
For more general information on Platform Units consumption for our AI products, check the Metering and charging logic and License tracking sections.
For specific details on Platform Units consumption for Process Mining, check out the License page in the Process Mining guide.
You can also allocate and track Platform Units consumption at tenant level. Check the Allocating licenses to tenants page from the Automation CloudTM guide for more details.
This section contains specific information regarding Platform Units depending on the used activity, covering the cost for every AI product.
To calculate the overall consumption cost, the following formula is used:
prediction cost
+ hardware cost
= consumption
cost
For more information, check the following sections:
- Prediction cost
- Hardware cost
To calculate the prediction cost, the following formula is used:
input size
x unit cost of the model
=
prediction cost
Input size
Model | Input type | Input size | Computed input size |
---|---|---|---|
Document UnderstandingTM (UiPath and Customer-Managed third party) | Document | 1 page | Number of pages in the input document |
Communications Mining | JSON | 1 message | Number of messages per mailbox or ticketing system |
AI Computer Vision | Image | 1 image | Always 1 |
Task Mining | Dataset | 1 dataset | Always 1 |
GenAI Activities | String | String size limit is different for each model | |
Other models | JSON | 2000 characters = 1 unit | Ceil(length(input)/2000) |
File | 5 MB = 1 unit | Ceil(size/5MB) | |
Files | 5 MB = 1 unit | Ceil(sum(size(input))/5MB) |
Model used
Model | When we charge | Platform Unit cost |
---|---|---|
Document UnderstandingTM (UiPath and Customer-Managed third party) | Per prediction | For a list of all Document Understanding models, check the Metering & Charging Logic page from the Document Understanding guide. |
AI Computer Vision | Per prediction | 0 |
Models in preview (like UiPath Image Classification) | Per prediction | 0 |
Task Mining | Per successful pipeline | 1000 |
Communications Mining | Per message uploaded, modified, or predicted | 0.2 - for more information on Communications Mining charging logic, check the official documentation. |
UiPath Light Text classifier | Per prediction | 0.04 |
UiPath Multilingual classifier | Per prediction | 0.1 |
UiPath Custom Named Entity Recognition | Per prediction | 0.1 |
Open Source packages |
Per prediction | 0.02 |
GenAI Activities | Per execution | 0.2 - without Context grounding
0.4 - with Context grounding |
The hardware cost at the time of deploying ML Skills is calculated as follows:
replicas
x resource cost
The default replica count depends on the account type:
- Enterprise account: 2
- Other account types: 1
Hardware | Platform Units Cost |
---|---|
0.5 CPU 2 GB RAM (default) | 0.2 Platform Unit / replica / hour |
1 CPU 4 GB RAM | 0.4 Platform Units / replica / hour |
2 CPU 8 GB RAM | 0.8 Platform Units / replica / hour |
4 CPU 16 GB RAM | 1.6 Platform Units / replica / hour |
6 CPU 24 GB RAM | 2.4 Platform Units / replica / hour |
GPU | 4 Platform Units / replica / hour |
For hardware cost related to Pipelines, check the following table.
Hardware | Platform Units Cost |
---|---|
CPU | 1.2 Platform Units / hour |
GPU | 4 Platform Units / hour |