Forum Discussion

vatojavier's avatar
vatojavier
Cloud Apps
09-01-2025

Sisense Intelligence token estimation

Hi.

We are considering activating Sisense intelligence to use a LLM for our data models and dashboards.

We want to estimate how much this would our organization from the LLM provider side. It depends on the tokens that are input into the model. In the Sisense documentation it mentions that depends on the number of tables and column of the model, but I guess also on the pre-instructions text that is sent along the user's input.

Is there a way of knowing how many tokens are added, or how much would cost to create a medium size dashboard given the OpenAI pricing?

Thanks,

Javi.

administration
Customer Outreach
dashboards & reporting

4 Replies

  • yaellev1's avatar
    yaellev1
    Sisense Employee
    09-02-2025

    vatojavier​ that is correct, both the user prompt and some system instructions are passed to the llm along with the datasource semantic metadata , contributing to the overall token count. We plan to introduce in product analytics to help customers understand their average token usage this is not available at this time. This is currently on our 6 months roadmap.
    More information on what data is processed across different use cases can be found here:
    https://docs.sisense.com/main/SisenseLinux/data-flow-per-feature.htm?tocpath=Sisense%20Intelligence%7CData%20Handling%20-%20Securing%20AI%20in%20Sisense%20Intelligence%7C_____4

     

  • vatojavier's avatar
    vatojavier
    Cloud Apps
    09-03-2025

    Hi,

    Thanks for the answer. I have another question: Is there an additional charge when enabling Sisense Intelligence, or does the extra cost only come from the LLM provider?

    • yaellev1's avatar
      yaellev1
      Sisense Employee
      09-18-2025

      There is no extra charge. Note that Sisense Intelligence includes both features that require an LLM and those that do not. So features like Explanations, Forecast, Exploration paths etc have always been available and do not consume tokens.
      Only usage of LLM based features consumes tokens while you're actively using the feature. Nothing is processed in the background.