Databox
Agentic analytics platform for you and your agents.
4.9•15 reviews•2.9K followers
Agentic analytics platform for you and your agents.
4.9•15 reviews•2.9K followers
Databox is an agentic analytics platform that brings performance data from across your business together with consistent metrics and business context. Ask its AI Analyst questions about your business, use Routines to surface important changes automatically, and turn insights into reports that explain what happened and why it matters. Databox does more of the recurring reporting and analysis, so you can understand performance faster and take better-informed action.
This is the 11th launch from Databox. View more
Databox CLI
Launched this week
Create data sources, load data, build metrics, and automate workflows directly from your terminal. Use 90+ commands yourself, or let AI coding agents like Claude Code, Cursor, and Codex do the work with 10 ready-to-use agent skills.
Free Options
Launch Team / Built With
Render Sandboxes: a computer for every agentRun untrusted code safely. Idle sandboxes cost nothing
Promoted
Metabase
We kept things simple and predicable.
Every CLI command maps directly to the @Databox public API. No hidden magic or extra layers of abstraction to figure out.
I think this becomes especially important when you start letting AI agents execute commands on your behalf. You want to understand exactly what is happening behind the scenes.
And since its fully open source under MIT, you can check the implementation yourself 🚀
We built this because we kept seeing agents get stuck at the same point. They could write the code, but they couldn't touch the Databox setup. With the skills, an agent can go from 'track this' to a data source, a dataset with the right schema, and data flowing in, all in one session.
I tested it on a finance monthly report we update every month from a CSV export and Excel. I asked Claude Code to set up a dataset with the right columns and load the file. With skills installed, it picked the commands, defined the schema & checked that the import went through. Next month it's the same command with a new file. Works well, great!
@tadej_kelc Love this, Tadej - that’s the workflow we had in mind. Set it up once, then it’s one command each month. One tip for recurring files: set a primary key on the dataset (--primary-key). Then if a month’s file gets re-sent or corrected, matching rows get updated instead of duplicated.
This fits how I actually work — most of my data starts in a script, not a dashboard, so piping JSON straight into a dataset from a nightly job is the part that caught me. That's the first thing I'd hand over to it. With 91 commands mirroring the API, do the agent skills end up being how most people actually use it day to day, or do you still find yourself reaching for the commands directly?
@jcbuilds Both, and they split nicely. The skills shine for setup and one-off work: creating the dataset, defining the schema, building metrics, or digging into something you haven’t touched in a while. Once the pipeline is set, the nightly job itself is best as a plain command. No agent needed, same result every run.
For your case that looks like: let the agent set up the dataset once, then have the script run databox dataset ingest <id> --file output.json each night with DATABOX_API_KEY set. Two things to keep in mind: batches cap at 500 records, and adding --idempotency-key makes a rerun after a failure safe.
Awesome work, team! 11th launch in the 11th month. I'm not a big fan of angel numbers, but let this be the lucky one for you ;)
@fedulovelena Thanks Helen! We’ll take all the luck we can get. Fingers crossed the numbers are on our side today. 🍀
Nice having all the skills already built into the CLI. Best of luck with the launch today.
@codeandsea Thanks Brent! That was the goal - install the CLI, add the skills, and your agent is ready to work with your Databox data. No extra setup or wiring needed. Appreciate the support today!
Congrats on the launch!
@neo_tiangratanakul Thanks Neo, appreciate the support!