AI data privacy

Several features in Omni are powered by AI, allowing you to use natural language to ask questions about your data, get help creating queries, build calculations, and more.

LLM providers

Omni uses two LLM providers to power its AI features:

• Amazon Web Services (AWS) Bedrock
• OpenAI

note

Any data, including metadata, provided to the LLMs used by Omni will not used for training.

User prompt categorization

When a user enters a prompt, Omni will first use AWS Bedrock's hosted Claude model to categorize the request to determine how to respond.

Shared data

To determine the correct category for the prompt, Omni shares the prompt itself with AWS Bedrock. Specifically, this is the natural language question or prompt provided by the user. For example, "How many users signed up last month?" or "Filter by the last two years."

Query generation

When generating a query, the output of the AI's processing is a new Omni query, which is a collection of metadata - including field names, filters, sorts, pivots, topic name, and limit - that is translated into SQL. This new query is then run within the current workbook to provide an answer to the user's prompt.

Because the AI uses an abstract query format and not SQL to create queries, the generated query respects the permissions set in Omni. This means it's not possible to access data outside of the topics, models, and connections a user has been restricted to in Omni.

Additionally, this approach ensures that no private, relational, or result set data is shared. Only metadata about the current query, user prompt, and selected topic fields is sent to AWS Bedrock, thus maintaining the privacy and security of your data.

Shared data

While relational data is never shared, Omni does share certain metadata with AWS Bedrock to generate accurate responses. This metadata includes:

Description	What's shared?
Current query metadata	Information about the currently selected query in the workbook, such as field names, sorts, limits, pivots, and filters
User prompt	The natural language question or prompt provided by the user. For example, "How many users signed up last month?" or "Filter by the last two years."
Context (ai_context)	Free text that provides context. This is set at the topic or view level using the ai_context parameter.
Fields within the selected topic	Metadata about the fields in the currently selected topic, such as field names, labels, descriptions, data types, and whether they're aggregates (count, sum, average) or dimensions. Note: Even if a user has access to multiple topics in a workbook, only metadata for the topic that's currently selected is accessed.

Workbook calculations

Omni uses AWS Bedrock to generate calculated fields.

Shared data

Omni will share the metadata for the current query to generate accurate formulas.

Data summarization

Omni's AI uses AWS Bedrock to power its data summarization features, which includes using the AI summary visualization or the query helper to summarize the results of a query.

Shared data

note

Models are region-specific to ensure data privacy. For example, if you're based in the EU, the models you use will be deployed in an EU-based region to ensure your data never leaves your region.

To generate accurate summaries, the following is shared with AWS Bedrock:

• The metadata for the current query
• A CSV of the current query's results

All data will remain within AWS.

Feature reference

The following table details each of Omni's AI features and the LLM(s) it uses. Refer to the AI settings reference for information about enabling and disabling these features.

Note: For AWS Bedrock, items marked with an asterisk (*) indicate that data is shared with AWS only for prompt categorization purposes.

Name	AWS Bedrock	OpenAI
Workbook calculations	Yes ✓	No X
Workbook query helper	Yes ✓	No X
Blank workbook jumpstart	Yes ✓	No X
Visualization helper	Yes* ✓	Yes ✓
IDE assistant	Yes* ✓	Yes ✓
Data summarization	Yes ✓	No X
AI summary visualization	Yes ✓	No X