At this stage, we're putting a lot of effort into "selling" the (free) community tier because (1) that leads to great feedback and (2) the vast majority of paying customers come from the free tier anyway.
We want the free tier to be so good it becomes the new notebook standard - and then we'll only charge for features that companies need, like Slack integrations or a large number of seats.
Regarding AI, we currently go with GPT-4o by default, but you can change it on the settings panel. Currently, we have only enabled GPT-4o and Mistral though, but we want to add more - it's just not our priority right now because the OpenAI model is just incredibly good.
I strongly agree with your comment. I'm a software engineer and I was surprised to find out about the practices of some data teams.
I do believe we should bring software best practices to the data world, not only regarding code design but regarding infrastructure and tooling too (like versioning everything).
Still, I get where they're coming from. A software engineer would also be frustrated if they had to learn everything a data scientist knows (probably even more).
I think the tooling itself can solve this issue by encouraging best practices though.
The data itself is indeed a problem. More than that, I'd add that the very definition of what's being measured or calculated is an even bigger problem (i.e. what's an active user?)
Still, I think that we can get to a place where everyone uses the same tool to collaborate on data matters, like a "Retool for data/BI". At a high-level, that's the direction we're going, and we're starting with notebooks and dashboards.
Just my 2 cents. Somehow got a chance to look into the competitive landscape. And found that which ever ICP to start with there's no immediate reason for adoption.
But who knows? Back in 90s no one knows they need an iPhone. Wish all the luck for your journey onwards.
I really appreciate the positive feedback, I'm glad you like the launch.
Regarding self-hosting: Yes, we have discussed that with other potential customers.
If you're interested in a self-hosted offering, please reach out to me at lucas.costa [at] briefer [dot] cloud and I'll help you out there and walk you through what that would look like.
In Briefer you can hide the blocks you don't want others to see, like the ones in which you're just manipulating data. Instead, you can show only the results so that your analysis is really easy to understand.
You can also display your analyses as dashboards or build small data apps with inputs and dropdowns for them to use.
Still, I wouldn't recommend completely non-technical users to create content within Briefer - only to read it and interact with the apps/dashboards there.
The products are similar in the sense that both are cloud-based notebooks, but we have different approaches to building them.
I answered a question about Hex below, and the general outline applies here. To summarize:
1. We want to go beyond just notebooks. We want to centralize all data tasks in Briefer, including traditional BI so we’re building specific features for that, like dashboarding and everything that comes with it.
2. We’ll enable people to use their own compute for the notebooks.
3. We want to allow people to manage notebooks, dashboards, and apps “as code” so they can version it whenever necessary.
We unfortunately didn’t finish items 2 and 3 yet because we’ve only started working on Briefer six months ago, but we’re fast and we’ll get there soon.
Also, we’re working on something new that will make the distinction clearer, but I can’t talk about that yet.
Hey there, CEO of Deepnote here. It looks like we are thinking about this very similarly, as all 3 points are something that we are already doing or will be shipping in the coming weeks. Either way, good luck with Briefer and happy to chat about our learnings building all of these things.
That’s possible. For it to work you’d have to create a “dropdown block” and select the “dynamic” option in its settings. Then, you will be able to select a dataframe and the column from that dataframe you want to use as dropdown options.
By the way, every query automatically becomes a dataframe so you can use either a query result’s column or a raw Python dataframe.
As a side note, I’m putting together detailed product documentation this week too and I’ll make sure to include it there.
It's not as much of a direct competitor because Count's approach seems more like "Miro for Data" while ours is more like "Notion for Data".
Still, I do think people could end up comparing both our tool and theirs when evaluating a few types use cases.