Data
Data Extraction
Pull structured fields from PDFs, exports, and semi-structured sources.
View template →Use case
AI Agents for Data Analysis
Recurring reports and ad-hoc questions pile up on a few analysts - while business teams wait days for numbers that should be self-serve.
The challenge
- Every weekly business review repeats the same SQL and spreadsheet gymnastics with small parameter tweaks.
- Dashboards show charts but not the narrative executives need to explain variances to the board.
- Data lineage is fuzzy: stakeholders cannot tell which export fed which slide when numbers are challenged.
The AgentWorks solution
AgentWorks data extraction agents pull from warehouses, CRM exports, and finance systems using governed connectors and row-level rules. Scheduled runs refresh the same canonical datasets analysts already trust - without emailing CSVs around.
Report generator agents turn metrics into written summaries: what moved, likely drivers, and recommended follow-ups. Trend analyzer agents highlight anomalies before they become surprises, with links back to underlying queries or visual snapshots.
Dashboard agents answer natural-language follow-ups against curated semantic layers, so product and ops leaders explore safely without learning SQL. Each answer records the definition used, supporting reproducibility when finance reconciles figures.
Analysts graduate from report factory to partner: they curate models, validate agent outputs, and tackle deep dives while automation handles the long tail of repetitive cuts. Governance stays intact because access policies live in one place.
Workflow in four steps
Connect sources
Define approved tables, metrics, and refresh windows for agents to query.
Extract & validate
Agents pull fresh slices, reconcile to control totals, and flag schema drift.
Analyze & narrate
Trend and variance commentary is drafted with charts and source references attached.
Distribute & iterate
Reports publish on a schedule or trigger from chat; feedback loops refine prompts and definitions.
Worked example
Monday-morning revenue variance pack
- Agent
- Data Extraction Agent, then Trend Analyzer Agent and Report Generator Agent
- Input
- A scheduled pull from the connected warehouse and CRM export, scoped to the tables and row-level rules your admin approved.
- Approval gate
- Extraction reconciles to control totals automatically and flags schema drift as a review task rather than silently publishing a broken number - an analyst confirms the reconciliation before the narrative step runs. The generated variance commentary is reviewed by the analyst before distribution.
- Output
- A written summary of what moved and likely drivers, with each figure linked back to the query or snapshot that produced it, delivered to a channel or inbox on schedule.
Relevant agents
Start from proven templates - each opens a full detail page with deployment notes and related agents.
View Data Extraction agent template View Report Generator agent template DataReport Generator
Turn metrics and narratives into stakeholder-ready reports.
View template →View Trend Analyzer agent template DataTrend Analyzer
Spot patterns in time series and highlight anomalies worth action.
View template →View Dashboard Agent agent template DataDashboard Agent
Explain charts, drill-downs, and KPI movements in plain language.
View template →
Results & benefits
Minutes, not days
Recurring packs generate on a timer with consistent structure and sourcing.
Clearer storytelling
Narratives alongside charts help leaders explain movement without analyst shadowing.
Traceable numbers
Each insight links to queries and snapshots so debates resolve with evidence.
FAQ
Frequently asked questions
- Which agent templates cover data analysis and reporting?
- Data Extraction Agent pulls from governed connectors on a schedule, Report Generator Agent turns metrics into written narrative summaries, Trend Analyzer Agent highlights anomalies with links to underlying queries, and Dashboard Agent answers natural-language follow-ups against a curated semantic layer.
- Does the agent have raw access to all our data?
- No - Data Extraction Agent only queries the tables, metrics, and refresh windows your admin explicitly approves via governed connectors and row-level rules. It does not get broader warehouse access than what is configured for its connector.
- How do we trust a number an agent reports?
- Every figure in a Report Generator Agent narrative or Trend Analyzer Agent flag links back to the query or snapshot that produced it. When stakeholders challenge a number, you open the linked source rather than re-running the analysis from scratch - that traceability is the point of the workflow, not an add-on.
- What happens if source data changes shape unexpectedly?
- Data Extraction Agent reconciles pulls to control totals and flags schema drift as a review task instead of silently publishing on stale or broken assumptions. A human confirms the reconciliation before downstream narrative or dashboard steps run on that data.
- Can non-technical stakeholders query data themselves?
- Dashboard Agent answers natural-language questions against a curated semantic layer you define, so product and ops leaders can self-serve without writing SQL. Each answer records which metric definition it used, which matters when finance needs to reconcile a number later.
- How is data analysis automation billed?
- Extraction, analysis, and report-generation runs draw from your workspace wallet balance per execution. A full scheduled variance pack costs more than a single ad-hoc Dashboard Agent question because it chains more agent steps; per-run cost is visible in the activity log.
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