Databao is a team of AI data coworkers that learn how you work, take on your data tasks — cleaning, analytics, reports, and monitoring — and run them end to end. They run locally on your machine.

Does my data leave my machine?

No. Databao runs on your computer and stores and analyzes everything locally. Anything that would leave your machine is called out and waits for your approval.

How does Databao learn a task?

Show it one cycle — your data sources, spreadsheets, past reports, and the steps you do by hand — or walk it through in chat. It learns the task and gets better every time you review.

Can I audit what the agents did?

Yes. Every task keeps a complete, local audit trail: each step against the plan, every input, where it came from, and the file it produced. You can export a signed log at any time.

Databao

baked by

Self-improving agentsthat know your dataand run your data tasks

Benefit from agents that know your data, run your tasks, and work locally as a Desktop app. They learn your sources, your transformations, and the questions you would typically answer yourself.

Tell us what your data tasks look like and what you want to automate.

Delegate your data workflows

Each agent specializes, remembers your process, and works on its own — and they all live inside one workspace.

Databao — Annaclaude-sonnet · local

Anna10:41

It's the start of the month — your May sales report is due. Want me to pull all 6 sources, clean and join them, and assemble it like last time?

You · 10:42

Yes, go ahead.

Anna10:42

Done — I pulled all 6 sources, cleaned and joined them, and assembled the report. Attached below.

sales_report_may.pdf2.4 MB · PDF document

monthly_sales_report · completed

Message Anna…

Anna prepares your reports.Anna knows which six sources feed the monthly sales report, how they're cleaned and joined, and what the output looks like. You taught her once. Now she compiles the report on schedule and sends you a draft.

AnnaJob

Reporting agent

sales_report_may.pdfdraft

PDF

Joe monitors your metrics.Joe knows which KPIs matter and what their normal ranges are. When something changes, he finds the driver and emails you before the review meeting.

Joe

Monitoring agent

KPI monitorrevenue · 30d

Mira runs your analysis.Ask Mira questions in plain language. She writes and runs the queries, checks the joins, and returns findings with the SQL attached. When ready, enable Mira for your stakeholders directly via Slack integration.

Mira

Analytics agent

exploring dataset12,480 rows

What your agents handle

Pick a task and have them run it end to end, including:

Data cleaning and prep

Exploring, deduplication, joining, and reshaping raw exports.

Self-service analytics

Asking questions in plain language and getting queries you can actually read.

Recurring reports

Extracting, merging, and preparing on a schedule.

Multi-source consolidation

Working across six systems in one consistent view.

Root-cause analysis

Identifying the drivers behind shifts in metrics, with evidence.

Anomaly monitoring

Flagging issues before someone screenshots the dashboard.

And more…

How an agent learns a task

Weekly KPI Report · last cycle

Connected

Final report & workbook

Source exports (6)

Request & reminder emails

Templates & instructions

What Databao learned

Which sources feed each metric and when they refresh
How raw data is cleaned, joined, and reshaped
How the final report is assembled from the sources

How Databao compares to the alternatives

A team of data coworkers built for the work — not a general assistant you have to babysit.

Criteria	Databao	General agents (OpenClaw, Hermes)	Claude / ChatGPT
Built for data work	30+ purpose-built data connectors	A data layer you build yourself	General chat
Context	Knowledge of your schema and tasks; memory of your corrections	Skills created by hand; generic self-improvement	No memory; context must be provided every session
Execution	End-to-end scheduling; exceptions presented for review	Cron + DIY setup	Basic scheduled tasks
Verifiability	Signed local audit trail; every source, transform, and query logged	None	None
Data boundary	Runs on your machine; guardrails and access controls	None built in	Servers that receive your data

Start solo, then share

Everything runs and is stored on your machine. When a workflow proves out, share the agent's skills and task definitions with the team. That way, the next analyst gets a working pipeline instead of a knowledge base page.

Start Personal

Everything runs and is stored on your computer. Databao uses local or cloud models, whichever you choose. Nothing leaves your machine unless you allow it.

On your machineLocal or cloud models

Go Team

Everything from the personal setup stays. On top of that, you add a shared knowledge layer: your coworkers' skills and data workflows are shared across the team.

Share data workflows across the team
Reuse skills the team already trusts
Build an accurate map of your team's data work

Works with the data sources your work already runs on

Connect the databases, warehouses, and apps you already use. Databao reads from them directly — no migration, no new pipelines to wire up.