Pricing
To create and use a knowledge base, T tokens are needed. A T token is the pricing unit common for all types of expenses in Tovie Data Agent.
Upon registration, you’ll receive 1,000 T tokens for free. When the tokens run out, purchase a token package to continue utilising the knowledge base. You can check and top up your token balance on the Account page.
To view statistics, check your balance, and top it up, you need the BILLING_ADMIN role.
For more information about this role, see the General roles section of the Tovie Cloud documentation.
T token packages
| Cost | Package size, in T tokens |
|---|---|
| $5 | 666.67 |
| $10 | 1333.33 |
| $40 | 5333.33 |
Corporate clients benefit from tiered pricing: larger packages offer greater savings. If interested, contact us at contact@tovie.ai.
T token usage
You can see how T tokens are spent in the Statistics section of the knowledge base project.
The most up-to-date pricing information is available only on this page. Knowledge bases cannot provide precise information about their usage costs.
Requests to LLM
A knowledge base sends requests of several types to an LLM:
-
User requests: to rephrase a user’s question to the knowledge base and to generate a response. Questions in the test chat, in channels, and via API are considered here.
-
Agent requests: to retrieve chunks if the chunk retrieval method using LLM is selected in the settings.
-
Quality evaluation: to generate test sets and perform evaluations.
-
Chunking:
- To split text into chunks, if LLM-based chunking is selected.
- To enrich chunks with additional information and obtain image descriptions, if these options are enabled.
Request costs in T tokens depend on:
- The language model selected.
- The length of the request (including context) and response.
| Model | Cost per 1,000 tokens for the model, in T tokens | |
|---|---|---|
| Input ↑ | Output ↓ | |
| DeepSeek-V3 | 0.27 | 1.1 |
| GPT-4o | 2.5 | 10 |
| GPT-4o mini | 0.15 | 0.6 |
| Qwen2.5-32B-Instruct-fp8-dynamic | 0.625 | 0.625 |
Data storage
The cost of storing source documents is 0.756 T tokens per GB per day (23 T tokens per month).
If your T tokens run out, the files are stored for another 30 days and then deleted.
Vectorisation
Vectorisation is the conversion of text into numerical vectors. It applies to both your data during the indexing stage and to user queries.
The cost depends on the vectoriser model selected:
text-embedding-3-large: 0.13 T tokens for 1,000 model tokens.intfloat/multilingual-e5-large: 0.1 T tokens for 1,000 model tokens.
Website parsing
For website integration, the processing cost is 11 T tokens per page.
Speech recognition
Speech recognition costs 6 T tokens per minute.