AI assistant data handling

Target Audience: Developers building AI chat or embed experiences with Toucan AI.

TL;DR

• The AI assistant processes your questions, database metadata, and query results to answer and build visualizations.

• Conversation history is stored on the platform so users can continue a thread.

• Sub-agents (query building, chart building, exploration) run in isolated steps; only the main assistant thread keeps long-lived history.

• Third-party AI providers may receive prompts and context when AI features run — see Third-party subprocessors.

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When to use this

Use this page when assessing privacy impact of AI chat, what may be retained after a session, and what may be sent to external AI services.

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What the assistant processes

During a conversation, the assistant may use:

• User messages and assistant replies

• Database metadata (table and column names, descriptions) to understand your data model

• Query results from your connected database (for example previews or aggregated answers)

• Optional context from your embed integration (non-identifying clues you provide)

Query results used in AI workflows are fetched on demand from your database; they are not bulk-downloaded into a Toucan data store. See Data storage & retention.

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What the assistant stores

Item	Stored?	Notes
Conversation messages	Yes	Per user/thread; can be cleared in product
Structured “plans” for complex tasks	Yes	Linked to the conversation thread
Full copy of your database	No	Queries run against your DB when needed
Query result rows (platform-wide cache)	No	Results may appear inside a stored conversation

Clearing a conversation removes that thread’s stored assistant history.

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Third-party processing

Depending on configuration, AI requests may be processed by:

• An LLM provider (for example Mistral or another provider configured for your deployment)

• Analytics or tracing tools (for example product analytics or execution tracing)

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Best practices

• Do not include personal data in optional AI context fields.

• Use row-level security so the assistant only queries data the end user is allowed to see.

• Clear conversation history when your product requires it (for example on logout or account closure workflows you implement).

• Review subprocessors if your compliance program requires a register of external processors.