Hey 👋 We're launching Velvet's new AI SQL editor today!
We made Velvet to solve our own problem. As an early-stage startup, we're built on top of Supabase, Stripe, and other tools. We needed an accessible way to unify data and run queries. Velvet lets any team member access real-time data, write complex SQL with AI, and turn those queries into re-usable components.
We've got an amazing group of early adopters already using it daily, and we hope you'll try it out!
🧑🏻💻 Connect databases, sync third-party APIs, and collect events
🔮 Ask natural language questions to write complex SQL with AI
💚 Save queries to share, visualize, or create API endpoints
Use Velvet to experiment, ship, and scale faster. Try it out at usevelvet.com, and share your feedback or questions below!
Use code TRYVELVET for 25% off after your free trial.
Everything Chris builds is great! And this makes me feel so much better for never getting good at SQL.
Congratulations on launch @emmalawler24 and @chris_hendel!
I've been beta testing Velvet for a couple of months, and I'm excited to see it go live.
Every startup reaches a point where they outgrow Amplitude or Mixpanel. These tools enforce specific data structures, and their SDKs get blocked by many browsers. They completely break with multi-tenancy and barely support organizations.
The best-in-class in-house analytics stack is Snowflake, Fivetran, and PowerBI. However, this costs about a quarter million dollars, and requires hiring a data team to maintain and analyze it. This stack can answer any question you want, but PMs lose the ability to easily ask questions directly.
Velvet bundles this warehouse/import/analysis stack, and sprinkles in amazing UX and AI to make it modern. Now, any startup can build an advanced data analytics stack that answers any question in their data, and its AI editor makes the product easy enough that PMs can self-serve questions - no data analysts required.
In the age of AI, controlling your data is key. Velvet centralizes your databases, third-party events (like Stripe), and even first-party events from your app - storing them in one place and letting you write queries that join across sources.
Woah, this is so impressive ! Writing SQL queries can be such a hassle. It's a clever application of AI.
Would love to try it !
Very solid execution, powerful and very well designed. Great use of AI, getting SQL written for you is super useful.
Congratulations on the launch! Having all my data in one place and being able to query it easily sounds incredibly useful. And the fact that I can use an AI editor to make my data accessible and interoperable is just icing on the cake. Great job!
Congrats Velvet team! Such an easy product to use and adds to much value to product & eng teams
I haven't yet tried the new version but I've been impressed with how consistently the Velvet team has learned, iterated, and shipped since we first chatted a year ago.
I can see this approach replacing the request-export-spreadsheet workflow that hampers a ton of data-informed decision making for a lot of people.
- It's great for startups that don't have a full data team in place
- It's also great for larger cos with dedicated analytics engineering practitioners building data assets to be used downstream
The potential for enabling (and upskilling) power users is pretty exciting.
Big congrats on the launch Emma and Chris. Velvet looks great. Good luck to you today ❤️🦄
Really impressive, congrats at all team! Day after day seeing products like Velvet I think the time when everyone will be able to program is approaching. It will change the world and the way we do business. I heard a recent interview with the CEO of NVIDIA on this very topic.
About Velvet on Product Hunt
“Make everyone a data engineer”
Velvet launched on Product Hunt on February 27th, 2024 and earned 157 upvotes and 32 comments, placing #13 on the daily leaderboard. Query all your data in one place and ship real-time product features. Use our AI editor to make your data accessible and interoperable.
Velvet was featured in Developer Tools (511.4k followers), Artificial Intelligence (466.8k followers) and Data & Analytics (5.6k followers) on Product Hunt. Together, these topics include over 158k products, making this a competitive space to launch in.
Who hunted Velvet?
Velvet was hunted by Emma Lawler. 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 Velvet stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Emma Lawler