AgentQ Overview

AgentQ is the AI assistant built into the Qualytics platform. It gives people and AI systems natural-language access to shared, governed context and the actions available through their Qualytics permissions. Powered by the Model Context Protocol (MCP) and the AI provider configured for your deployment, AgentQ can help you explore datastores, build transformations, create quality checks, investigate anomalies, and take other supported actions.

AgentQ supports your data quality work, but it does not replace your judgment. Review generated interpretations and platform changes before relying on them, especially when they affect business-critical or regulated data.

You can interact with AgentQ through the full-page chat opened from the left sidebar, the floating chat widget available on every page (toggle with Q), and the assistant embedded in quality check and check template dialogs. Before an AI provider is connected, the AgentQ page shows a live preview of what it does, headed Ask about your data. Act on the answer., with Easy setup and Custom setup cards for Managers and Admins and a note for everyone else that an administrator connects a provider once and it turns on for all. AgentQ is set up and managed from that page, under Manage in its sidebar. See Add Integration. The AgentQ API supports custom integrations, while external MCP-compatible clients (Claude Desktop, ChatGPT, Cursor, and others) can connect to the Qualytics MCP server.

Built-In Intelligence

• Smart Suggestions: when you start a new conversation, AgentQ generates personalized prompt suggestions based on your data assets and active anomalies.
• Context Awareness: AgentQ automatically detects the page you're on and injects relevant context (datastore, container, field, check, or anomaly) into the conversation.
• Review-Before-Save Proposals: In quality check and check template dialogs, AgentQ can propose settings from a plain-language request. Nothing is saved until you apply the proposal to the form, review the highlighted changes, and save the item. Only the most recent proposal in a conversation can be applied, so an outdated configuration cannot reach the form by mistake.
• Permission-Aware Actions: AgentQ uses your Qualytics identity and permissions, so it can only access data and perform actions available to your account.
• Co-Authorship Tracking: when a change is made with AgentQ's help, the item's own Timeline records the assistant as a co-author alongside you, providing a record of AI-assisted actions.
• Admin Audit Reporting: administrators can review workspace-wide AgentQ prompts, responses, tool calls, recorded actions, usage, and cost estimates for a selected date range and set of invoking users.
• Conversation Memory: long conversations are automatically managed through context compression, keeping recent messages in full detail while summarizing older context. See Conversations, Responses & Context for details.
• Background Streaming: if you navigate away while AgentQ is generating, the stream continues in the background. The response is waiting when you return to that session.
• PDF Export: export any AgentQ response as a PDF for sharing and reporting.

Description Suggestions

The sparkle control next to any description editor lets you request an AI-generated description built from the asset's metadata. It is only visible when an AI provider is configured under AgentQ.

Click the sparkle, review the suggestion in the preview area, and either accept it (Use this), regenerate for a different take, or dismiss it. When the description field already holds text you have not saved, the accept button reads Replace draft instead, so it is clear what the suggestion will overwrite. The suggested text only enters the description field when you accept it. Regenerating, dismissing, or navigating away leaves the current description untouched.

Where the sparkle appears

The suggestion draws on the metadata Qualytics already stores about the asset. It does not read live data rows.

What to expect

• Length. Suggestions are usually a sentence or two. They can run longer, and use headings and lists, when the asset has enough detail to justify it. The upper bound is the same 8,000-character limit that applies to any description you type yourself, so an accepted suggestion always fits the field.
• Same across surfaces. The interaction (sparkle to preview to Use this / Regenerate / Dismiss) is identical whether you are on a datastore, a field, or a quality check template.
• Language. The suggestion follows the language behavior of the AI provider and model you have configured. If you need to translate the result, edit the accepted text after using it.
• Retries. Each Regenerate click starts a new AI request and can use a different framing, such as the audience, business process, downstream impact, or consequence of missing data. Results vary by provider and model, so two attempts may still produce similar suggestions. Usage is subject to the provider and commercial terms configured for your deployment.

When suggestions are not available

Even with an AI provider configured, the platform can still refuse a suggestion in a few cases:

On most surfaces (Computed Tables, Computed Files, Computed Fields, Computed Joins, and Quality Checks), the sparkle uses the same permission as editing the description manually: if you can edit, you can also request a suggestion. Anomalies are an exception: the sparkle appears for anyone with the Reporter team permission (or above), even though editing the anomaly description itself requires Author. Archived anomalies never show the sparkle.

Deep Dive

How-tos

Reference