SQrL (pronounced as "squirrel") is an AI-powered co-pilot built by SingleStore that answers your questions and helps you code faster (in the context of SingleStore). It is trained using content from SingleStore documentation, GitHub, Forums, and other internal sources, to provide product-related information on SingleStore. SQrL is powered by OpenAI GPT-4.

In the Question and Answer mode, SQrL can answer questions and provide code suggestions for both the SingleStore Helios and SingleStore Self-Managed deployments.

Why Use SQrL

SQrL is designed to provide immediate and relevant responses to SingleStore-related questions. It can assist you with deployments, code optimization, integrations, resource management, troubleshooting, etc.


SQrL may sometimes return reasonable-sounding but inaccurate responses. To help us improve SQrL's accuracy, provide feedback using Thumbs down next to a response.

Getting Started with SQrL

a. SQrL Website

You can use SQrL in the Question and Answer mode on the SQrL website even if you are not a member of any SingleStore organization. SingleStore users on SingleStore Self-Managed deployments who do not have access to the Cloud Portal can also use this platform.

b. SingleStore Documentation

You can access SQrL in the Question and Answer mode from any page in the Documentation site. Select the (SQrL) icon on the side of the page to open the SQrL pane.

Access SQrL from the Documentation site.

SQrL Usage Mode

Question and Answer Mode

In the Question and Answer mode, SQrL answers the user's queries (questions). You can ask questions about learning new features, troubleshooting specific issues, comparing approaches to a specific use case, and more. The answers may include suggestions to related questions and a list of sources from where the response is derived. After you enter your query, select Enter/Return to submit it. To add another line to your query (add a new line), use Shift+Enter or Shift+Return.

You can also provide feedback on SQrL responses to help improve its accuracy. Select Thumbs up for positive responses and Thumbs down for negative responses and provide feedback.

To share a SQrL discussion, select Share. It shares the entire SQrL discussion. When you select Share, a unique URL is generated for the discussion session. Anyone with access to the URL can view the contents of the discussion. You can also copy a specific code snippet or other blocks from the discussion with SQrL without using the Share feature.

Select Clear to clear the current discussion. To stop a SQrL response, select Stop.

SQrL and Privacy

This section focuses on privacy practices, data collection, data security, and data retention in the context of SQrL only. Refer to Privacy Notice for information about SingleStore's privacy policy.

Data Collected by SQrL

SingleStore collects and processes data from SQrL to provide the service. SingleStore continuously improves SQrL by leveraging data collected from SQrL to provide more accurate responses to your queries. This data includes prompts, responses, and user engagement metadata. SingleStore retains some of the collected data for analysis and improvements. The collected data is not used to train large language models (LLMs).

SingleStore collects prompts, answers, and user engagement metadata from SQrL as follows:

  • Prompts

    A prompt is the contextual information that SQrL gets when a user asks a question/query. Prompts are transmitted in real-time and retained to improve our product and documentation on questions asked by users.

  • Responses

    SingleStore retains responses/answers from SQrL to improve the user experience of our product.

  • User Engagement Metadata

    When you use SQrL, it collects user engagement data. This data consists of usage information and events generated while interacting with SQrL. These events include, but not limited to: user actions like Thumbs up or Thumbs down, feedback, and feature engagement.

Sharing Collected Data

SingleStore shares the data collected from the SQrL discussions with the following AI providers (via API):

  • OpenAI

  • Azure OpenAI

  • Anthropic

The data shared with these AI providers is NOT used to train their AI models. For information on privacy policies of each of these providers, refer to the following links:

Data Security

Refer to Security for information.

Last modified: April 3, 2024

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