Turn any conversation with your AI Analyst into a polished report, slide deck, or interactive document built from your live data. Generate it from a single prompt, then share it via public link or download as a PDF.
I’m Pete from Databox. Today we’re shipping Artifacts inside Genie, our AI Analyst. An artifact is a report Genie generates from your connected data. It combines the charts you’d normally build by hand with the analysis of what actually drove the numbers, in one shareable document.
Reporting used to work like this... You’d build a bunch of dashboards. You’d compare performance to the previous period and to goal, try to understand how the work you did turned into the result you got. Then, you'd write out what happened and what you planned to do next.
Whether you hit the goal, missed it, or crushed it, the manual process was the same.
With Artifacts, none of that is necessary. It’s a one-time setup. You connect your data and define your metrics once. After that, you tell Genie what you did, and it compares performance to the previous period, checks whether the work correlated with what you achieved, digs into why through statistical analysis, and recommends what to do next. Then it builds the report.
A “what happened last month” question becomes a finished report in minutes.
A few very specific things it can do:
Turn the same report into a slide deck. One follow-up request, nothing rebuilt.
Restyle a report to your own brand or a client’s, mid-conversation.
If you're a professional services firm, build a cross-client report spanning every account, not one client at a time.
Ship as a public link, with no login for whoever you send it to, or a PDF. Turn the link off whenever you want.
You might be asking, why not just use Claude or ChatGPT? Because Databox already has your data connected, understands how to calculate your metrics, and knows how to run statistical analysis on them.
Three things the general chat tools don’t have or don't do consistently. Ask one of them for a report and you feed it the data yourself, every time, and hope it calculates and analyzes correctly. And when it gets something wrong, you’re stuck.
Databox artifacts are editable, so you add your own context and Genie refines it. Fine tuning, not redoing.
Less time spent reporting means more time doing the work and more time thinking about how to do it better. If you’re not on Databox yet, I challenge you to automate your next report in three steps.
1. Start a trial, 2. connect your data, 3. and ask Genie to “create a report analyzing what happened last month and why.”
The frozen-snapshot answer makes sense. The version I keep hitting is source data that restates after the fact: I generate a June report, share it, then re-trigger the same report in August and June's numbers have moved because an integration backfilled or a metric definition changed. The client sees two different Junes. Does Genie surface that the underlying data shifted between generations, or do you find out when someone asks?
no rush, honestly the fact that you'd rather confirm than guess on a data-loss question is the right instinct. that's exactly the kind of answer that's worse wrong than late. I'll keep an eye out for the follow up
The Databox MCP release fast-forwarded years of experience for the junior folks on the marketing agency teams I work with. Artifacts just took that to the next level.
I sit at the intersection of ops, strategy, delivery, and client services, and month-end analysis has always been the hardest thing to scale. Even once a junior analyst could get a real answer out of the data, someone senior still had to turn it into something you could put in front of a client. That type of redundancy eats away at account margin week after week after week.
This morning I asked Genie to build a marketing report on a client account. Sessions were up 45%, which is the number a junior AM might lead the client call with and stop there. The artifact tied that jump to four pages we shipped during the month, then flagged that search visibility had actually declined over the same window, so the growth was coming from social and direct rather than search. Real traffic, but it doesn't compound the way search does. The first of six recommendations was to get the remaining pages live so it starts to.
That's a senior strategist's output, and anyone on the account team can produce it on their own now.
Really excited to see where this goes with the rest of the roadmap!
How customizable are the reports? Can teams define their own metrics and reporting structure?
Congrats on this Artifacts launch.. it will definitely help in easy visualisation and analysis .. just one question, would it go deeper to identify outliers..
honestly this looks pretty solid, especially for teams that don't want to deal with a clunky BI setup. one thing i'd love to see is a built-in anomaly alert system that flags weird spikes or drops in your custom metrics straight to slack, basically instead of having to dig through dashboards yourself. would save a ton of time.
This one clicked for me right away. You tell Genie what you actually did, so the report explains the result instead of just restating it. Dashboards were never the bottleneck. Nice work.
Congrats on launch #8, Pete and team. The part I like is that it doesn't stop at the chart - it packages the analysis into something you can actually hand to someone. That last mile of turning an answer into a shareable artifact is where most BI tools quietly leave you. Nice work.
Would love a native "anomaly explanations" panel that shows the most likely contributing factors for each spike or dip detected, instead of just flagging the change. Would save me a ton of time compared to manually drilling into the data every time.
Turning an analyst request into a shareable report could remove a lot of reporting friction. Can readers trace every conclusion back to the underlying metric, source system, and transformation used by the AI analyst?
the edit-mode-vs-prompt-mode split is a smart way to avoid the "AI overwrote my wording" problem. question on that: once I've hand-edited a few sections and then ask Genie for a structural change later, is there version history I can roll back to if the new prompt mangles something near my edits, or is the artifact a single mutable document with no undo path back to an earlier state
congrats on the launch! is there a limit to how large the data sets can be/upfront usage? for example if I'm migrating from another tool could I upload my larve pre-existing data sets?
IMO, the most exciting launch recently. 🚀 It’s become the only way I’ve been doing analysis and reporting over the last couple of weeks.
Huge congrats to the team! This is just the beginning… can’t wait to see what’s coming next. 👀
This looks useful for teams that need to share reports quickly. Can you also trace each number back to the original data and filters when someone asks about it?
Being able to ask for the same analysis restyled for a different client's branding without rebuilding it is the part I would use most. Pulling from live data at generation time also avoids the usual stale screenshot problem. When a report goes out as a public link, does it refresh against live data on every view or is it frozen at the moment you generated it?
Hey all! Weighing in here. From a technical standpoint, what makes this reliable is where the data comes from. The artifact isn't summarizing a pasted export, it's pulling from your live connected sources across 130+ integrations. That's the difference between a document that reads well and one I can actually stand behind in a meeting 💪🏻
Don't get me wrong i like the idea, but what's the biggest difference between Databox and Cloude with proper skills?
This one lands at a good time for us. Half my week goes into turning dashboard numbers into something a client can actually read, so going from a question straight to a finished deck sounds great. For agencies running several accounts, can I save a house style once so every report comes out with the right branding by default?
About Artifacts by Databox on Product Hunt
“Ask your AI Analyst and get back a ready-to-share report”
Artifacts by Databox launched on Product Hunt on July 27th, 2026 and earned 433 upvotes and 97 comments, earning #2 Product of the Day. Turn any conversation with your AI Analyst into a polished report, slide deck, or interactive document built from your live data. Generate it from a single prompt, then share it via public link or download as a PDF.
Artifacts by Databox was featured in Productivity (657.3k followers), Marketing (466.6k followers), SaaS (43.4k followers) and Artificial Intelligence (475k followers) on Product Hunt. Together, these topics include over 389.7k products, making this a competitive space to launch in.
Who hunted Artifacts by Databox?
Artifacts by Databox was hunted by Rohan Chaubey. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Artifacts by Databox stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Rohan Chaubey
Hi Product Hunt.
I’m Pete from Databox. Today we’re shipping Artifacts inside Genie, our AI Analyst. An artifact is a report Genie generates from your connected data. It combines the charts you’d normally build by hand with the analysis of what actually drove the numbers, in one shareable document.
Reporting used to work like this... You’d build a bunch of dashboards. You’d compare performance to the previous period and to goal, try to understand how the work you did turned into the result you got. Then, you'd write out what happened and what you planned to do next.
Whether you hit the goal, missed it, or crushed it, the manual process was the same.
With Artifacts, none of that is necessary. It’s a one-time setup. You connect your data and define your metrics once. After that, you tell Genie what you did, and it compares performance to the previous period, checks whether the work correlated with what you achieved, digs into why through statistical analysis, and recommends what to do next. Then it builds the report.
A “what happened last month” question becomes a finished report in minutes.
A few very specific things it can do:
Turn the same report into a slide deck. One follow-up request, nothing rebuilt.
Restyle a report to your own brand or a client’s, mid-conversation.
If you're a professional services firm, build a cross-client report spanning every account, not one client at a time.
Ship as a public link, with no login for whoever you send it to, or a PDF. Turn the link off whenever you want.
You might be asking, why not just use Claude or ChatGPT? Because Databox already has your data connected, understands how to calculate your metrics, and knows how to run statistical analysis on them.
Three things the general chat tools don’t have or don't do consistently. Ask one of them for a report and you feed it the data yourself, every time, and hope it calculates and analyzes correctly. And when it gets something wrong, you’re stuck.
Databox artifacts are editable, so you add your own context and Genie refines it. Fine tuning, not redoing.
Less time spent reporting means more time doing the work and more time thinking about how to do it better.
If you’re not on Databox yet, I challenge you to automate your next report in three steps.
1. Start a trial,
2. connect your data,
3. and ask Genie to “create a report analyzing what happened last month and why.”
No coding, no spreadsheet-wrangling required.