A data analyst costs about $110,000 a year once salary and benefits are counted. A CellCog AI Employee queries your databases, builds live dashboards, finds the story in your numbers, and delivers analysis you can act on, for a fraction of that.
*A shift is a focused block of work, roughly 2,000 credits (about $20 at standard rates). One shift every working day, 250 days a year, comes to about $5,000 a year; actual cost scales with how much it works.
Five things a data analyst does every day, handled on demand.
Connect databases, spreadsheets, and analytics tools; it writes and runs the queries itself.
Build interactive dashboards that stay current, refreshed on a schedule as part of its routine.
Go beyond charts: segment, compare cohorts, and explain what changed and why it matters.
Turn analysis into clear reports, spreadsheets with real formulas, and presentation-ready documents.
Watch your key metrics shift to shift and flag meaningful changes before they become surprises.
Copy, paste, and adapt. Each one comes back as a finished artifact.
“Connect to our database and tell me: which customer segments grew last quarter, which shrank, and what changed. Build a dashboard I can check every week.”
Delivers: a segment analysis plus a live dashboard
“Here is a CSV of 12 months of sales. Find seasonality, our top products by margin, and three things we should do differently.”
Delivers: an analysis report with recommendations
“Our churn ticked up in May. Dig into the data and tell me which cohorts are churning, when in their lifecycle, and any common patterns.”
Delivers: a churn investigation with cohort breakdowns
“Build a financial model in a spreadsheet: revenue projection for the next 6 months based on our actuals, with assumptions I can adjust.”
Delivers: a spreadsheet model with live formulas
“Every Monday, refresh our KPI dashboard from the database and email me a summary of what moved and why.”
Delivers: a recurring dashboard refresh with a weekly summary
Founders stop exporting CSVs at midnight: the numbers arrive analyzed, with the so-what attached.
Small teams get real dashboards and honest metric readouts without borrowing engineering time.
Agencies deliver polished, data-backed reports for every client on a schedule, without a reporting team.
Knowing when to lean on a person is the whole point.
Knowing which anomaly is a data glitch and which is a business crisis often takes lived context.
Deciding which numbers to show the board, and how, is a human call.
It analyzes what it can reach. Tribal knowledge in someone's head stays out of scope until written down.
Hiring a data analyst is valuable, and expensive. Here is how it compares for the production-heavy parts of the job.
| Human Data Analyst | CellCog AI Employee | |
|---|---|---|
| Cost | ~$110,000/yr fully loaded | ≈ $5,000/yr* |
| Availability | Business hours | Works shifts on demand, any hour |
| Ramp-up time | 2 to 4 weeks | Instant |
| Output formats | A few document types | Reports, PDFs, slides, spreadsheets, images, video, audio, dashboards, interactive apps |
| Scalability | One person, one task at a time | Parallel tasks |
| Sick days and turnover | Yes | Never |
| Onboarding | Recruiting and training | Goals, access, and approvals |
| Turnaround on a new question | Days, queued behind other work | Same shift, most of the time |
| Dashboard upkeep | Decays after the first month | Refreshed on schedule, every time |
| Output formats | Charts and slides | Dashboards, spreadsheets with formulas, PDFs, full reports |
*A shift is a focused block of work, roughly 2,000 credits (about $20 at standard rates). One shift every working day, 250 days a year, comes to about $5,000 a year; actual cost scales with how much it works.
Yes, with credentials you control, and read-only access is the sensible default. It writes its own queries, and you decide what it can reach and can disconnect anytime.
Databases like MongoDB and PostgreSQL, spreadsheets, CSVs, Google Analytics, and hundreds of connected apps. If your data is reachable, it can usually work with it.
It shows its work: queries, assumptions, and methodology come with every analysis, so you can verify rather than trust. Computed values come from real code, not estimation.
Yes. It builds interactive web dashboards it keeps current on a schedule, and you can share them with your team.
BI tools visualize data after someone models it and builds the views. A CellCog AI Employee does that work itself: connects, queries, models, builds the dashboard, and explains what the numbers mean.
A data analyst costs about $110,000 a year once salary and benefits are counted. A CellCog AI Employee works in shifts of roughly 2,000 credits (about $20 each); one shift every working day, 250 days a year, comes to about $5,000.
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Point it at last quarter's data and get back the analysis, the dashboard, and the three decisions hiding in your numbers.