Data Quality Agent
Dataset profiling specialist
Profiles datasets, detects missing, duplicated or inconsistent values and produces a remediation report with prioritised fixes.
A sample-data demonstration workflow is available. Live execution needs more configuration.
What this agent is for
Make data problems explicit and fixable before they reach a dashboard or a model, without silently rewriting your data.
Capabilities
- Column profiling and type inference
- Missing, duplicate and outlier detection
- Referential and format consistency checks
- Rule-based quality scoring
- Prioritised remediation report
Inputs it needs from you
- CSV, Parquet or table extract
- Data dictionary
- Quality rules
Outputs it produces
- Profiling summary
- Issue register by severity
- Quality score
- Remediation plan
Industries
- Banking
- Healthcare
- Retail
- Telecom
- Government
- Energy
How This AI Agent Works
The published process for this agent: what triggers it, what it validates, which approved tools it calls, where a human approves and what it delivers.
Dataset profiling and analysis workflow
From an uploaded dataset to validated charts and a dashboard-ready report.
Saved with the run so the recorded execution trail shows what was asked. Demonstration runs use sample data. They do not touch your systems.
Public visitors can preview the structure and inspect every node. Labelled demonstrations and live runs require a signed-in account with configured providers.
Workflow summary as a text list
- 1. Upload dataset: Input. CSV, Excel or table extract uploaded to the workspace.
- 2. Validate schema: Validation. Check columns, types, keys and row counts.
- 3. Profile data: Approved tool. Compute distributions, nulls, duplicates and outliers.
- 4. Clean approved issues only: Decision. Fixes outside the approved rule set are proposed, not applied.
- 5. Analyse: AI agent. Answer the stated question and record the method.
- 6. Generate charts: Approved tool. Pick the chart type that matches each finding.
- 7. Validate metrics: Validation. Recompute headline metrics before publishing.
- 8. Dashboard and report: Output. Quality report, charts and cleaned dataset export.
Approval gate: none configured. Deliverable: Dashboard.
Workflow audit for this page
| Template ID | Nodes | Approval node | Output type | Preview | Demo | Live | Mobile test |
|---|---|---|---|---|---|---|---|
| data-quality-agent | 8 | No | Dashboard | Available | Available (signed in) | Available via Studio · requires ai_provider | Verified at 390px |
Demonstration runs are stored and replayed from recorded events. Live runs execute server-side in the Studio and only start when the listed integrations report healthy.
Ask this agent team a question
Ask the live agents
Describe the problem in your own words. We classify the industry, assign specialist agents, and you watch the workflow run and produce the visual deliverables — maps, dashboards, charts, tables and reports — instead of one block of text.
Demo mode uses clearly labelled sample data — never presented as verified.
Assigned specialists
Industry detected from your wording
- Requirement validation agent
- Analysis agent
- Quality and citation reviewer
Deliverables planned
Workflow the run follows
- 1. User request
- 2. Requirement validation
- 3. Industry classification
- 4. Specialist agent selection
- 5. Data and file collection
- 6. Tool authorisation
- 7. Execution plan
- 8. Multi-agent collaboration
- 9. Analysis or generation
- 10. Quality validation
- 11. Human approval
- 12. Visual deliverables
- 13. Monitoring and audit
Ready to scope your AI initiative?
Share your objective and constraints. A specialist reviews every request before any recommendation is issued.