Role-specific. Annual pricing. Anyone on the team can ping it.
A custom-built AI data analyst that lives in your team's Slack. Answers questions about the numbers, writes SQL against your warehouse, builds quick visualizations, and drafts the memo. Trained on your data model, your metric definitions, and your team's analytical style.
The data questions your team asks 20 times a week, answered.
Ask about the numbers in Slack, get the answer with the query, the chart, and the source.
Knows your schema, your dimensions, your common joins. Shows the query so analysts can verify.
Draws the chart inline in Slack for a Friday-quick read or drops it in your BI tool for permanence.
Pulls the data, writes the read, flags the caveats. Ready for an analyst to verify.
Pings when a key metric shifts week-over-week beyond your normal noise band.
Keeps definitions current, flags conflicting definitions across teams, drafts updates.
Deep, role-specific integrations. Not 3,000 shallow ones.
Warehouse
BI Tools
Modeling
Product Analytics
Spreadsheets
Communication
Docs
Need a tool not listed? Tell us during scoping.
Week 1
Week 2
Week 3
Week 4
Week 1
Week 2
Week 3
Week 4
Looker and Mode are your system of record for dashboards. Ash is the analyst who answers the questions your dashboards do not cover — the ad-hoc Slack question, the anomaly investigation, the board memo that needs a human read on the numbers.
Most teams run the fellow alongside their BI tool. Ash is the junior analyst you have not hired yet.
Each Data Analyst fellow is on a custom annual plan based on data model complexity and team size. Predictable annual price. No per-query meters.
Get pricing for a Data Analyst fellowAsh always shows the query. Hallucinated numbers are exposed by querying their source. We tune the fellow to flag uncertainty (small sample, ambiguous metric definition, missing data) rather than guess. Verify before publishing externally.
Generic text-to-SQL guesses your schema and your metric definitions. The fellow is trained on YOUR schema, YOUR metric dictionary, and YOUR common joins. Same general approach, very different accuracy.
It can draft a Mode/Hex/Looker dashboard structure and push the queries. Long-term dashboard maintenance is human work — analysts know which dashboards still earn their seat.
It flags them. If 'active user' means one thing in product and another in marketing, the fellow surfaces the conflict and asks which definition you want for this answer.
Tell us about your data. We will scope the fellow and have it in your Slack in about a week.