How AgentQ Works

AgentQ is an agent that works on your own Qualytics workspace. It is not a general-purpose chatbot with your data pasted into it. Every answer it gives is built by calling the same platform functions the web app calls, reading the result, and writing it up in plain language.

Where AgentQ Appears

AgentQ shows up in three places, all backed by the same configuration and the same conversation history.

How a Turn Works

A turn is one prompt and everything AgentQ does in response.

1. You send a prompt. AgentQ receives it together with the Business Context your administrator wrote and the earlier messages in the chat.
2. The model decides which platform tools it needs. It may call several, and it may call one, read the result, and then call another.
3. Each call appears in the chat as a step label while it runs, so you can see what AgentQ is doing rather than watching a blank space.
4. The model writes the answer from what the tools returned. Stop interrupts the turn, and whatever was produced is kept as a partial response.

Because the answer is assembled from live tool results, AgentQ reports what your workspace holds at that moment rather than what the model was trained on.

One Configuration for the Whole Deployment

The AI provider configuration is a single, deployment-wide setting rather than a per-user choice. A Manager or Admin selects the provider and completes any credentials it requires once, and AgentQ then becomes available to everyone with the Member role or higher. Only one provider configuration is active at a time.

The Business Context written during setup travels with every prompt, from every user, which is what makes the answers sound like they come from inside your organization. Do not put secrets or anything your provider should not process into it.

What AgentQ Is Allowed to See

Two limits apply at the same time, and the narrower one wins.

• The access level decides what kind of data may reach the model at all, from static guidance only, through metadata, up to values from your source data. It is set once for the deployment. See AgentQ Access Controls.
• Your own access decides which of your workspace's assets AgentQ may read on your behalf. AgentQ runs its tools as you, so a user restricted to a team sees only that team's datastores through AgentQ, exactly as they would in the web app.

When a question needs a tool the current level does not allow, AgentQ says so in the answer and explains what is switched off, rather than failing.

The Topic Guardrail

AgentQ includes an automatic guardrail that declines requests unrelated to data quality, governance, or the Qualytics platform.

What Is Allowed

Any request related to:

• Data quality, governance, management, or engineering
• Databases, datastores, tables, fields, schemas, or profiling
• Anomalies, quality checks, validation, or observability
• Transformations, ETL, computed datasets, or SQL
• Trends, metrics, insights, or quality scores
• Qualytics platform features and operations
• General greetings or help requests about AgentQ itself

What Gets Blocked

Requests clearly outside the data quality domain, for example asking AgentQ to write creative content, answer general knowledge questions, or perform tasks unrelated to your data infrastructure.

How Follow-Ups Are Handled

The guardrail includes up to 2,000 characters of prior conversation context when evaluating a new message. This means short follow-ups like "yes", "that one", or "the second datastore" are automatically recognized as continuations of an on-topic conversation and pass through without being blocked.

What Gets Recorded

Every chat is stored with its messages, so you can reopen it later and so administrators can review it. Prompts, responses, token usage, cost estimates, tool calls, and any platform changes AgentQ made are all available to Admins in the audit. See AgentQ Audit.

Archiving a chat keeps its record. Deleting one removes it, and its turns leave the audit with it.

See Also