Agentic Data Intelligence
Agents that watch the metrics. And explain the spike before you ask.
The next layer of analytics isn't a prettier dashboard — it's agents working underneath it. They watch the numbers, notice when something moves, dig into the why, and put the answer in front of you before you've opened the BI tool. New, real, and best built with someone who knows where the model breaks.
What's inside
The data team you don't have to hire.
- 01
Anomaly detection + investigation
Agents monitor your KPIs, flag the spikes and dips, and run the cuts to find what's driving it. You get the answer with the chart and the cohort attached.
- 02
Conversational analytics
Ask the agent in plain English; get the chart and the SQL. Grounded in your semantic layer so the numbers stay clean. Not a toy — actually trustworthy.
- 03
Auto-narrated reports
Combines with Automated Reporting — but with investigation built in. The Monday brief doesn't just show revenue; it explains why it moved.
- 04
Pipeline + data quality agents
Watch the warehouse for broken joins, missing rows, schema drift. Catch the data issue before the dashboard does — and before the CEO does.
How an engagement starts
Pick one workflow. Build it real. Expand.
- 01
Use-case scoping
Pick the agent worth building first — usually anomaly investigation or conversational analytics for the leadership team. Scope it tight.
- 02
Build + evaluate
Built on Claude with tool use against your warehouse, scoped to a small set of metrics. Evaluation set first; ship only after it passes.
- 03
Roll out + monitor
Live to a small group. Watch the traces, tune, expand. Monitoring catches drift; you stay close enough to fix what breaks.
Free 30-min review. We pick one agent worth building first.
Common questions
- Is this just a fancy BI chatbot?
- No. A chatbot answers questions if you ask the right one. These agents notice the issue first and start the investigation — different shape of work.
- Which models?
- Claude for the agent reasoning (best at multi-step tool use in 2026). The semantic layer is the source of truth, not the model.
- Is the data safe?
- Yes. The agent runs against your warehouse with scoped permissions; nothing leaves your environment that isn't already governed. Same access model as a junior analyst.
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