Zerve’s Data Science Development Environment gives data science and ML teams a unified space to explore, collaborate, build and deploy data science & AI projects.
Hey Product Hunt!
Over the last decade, I've been watching organizations struggle to build AI, most recently as CCO at DataRobot.
Things like unstable development environments, no real ability to collaborate with your team, and significant challenges in getting experiments into production are incredibly common and in many cases have become the de facto standard.
Our team has been researching and building a solution to these problems for over two years, and I’m really excited to share that with you today.
Zerve is a data science development environment for data science & AI teams to explore, build, collaborate and deploy their work. Imagine the best parts of Jupyter, VScode and Figma, that's Zerve!
Data exploration, but it's always stable
Notebooks were never built for productionizing your work and are fundamentally unstable. Instead, for the first time, explore you data and write stable code at the same time.
Figma like collaboration with VSCode like engineering controls
Zerve enables data teams to collaborate but in a safe and stable way. Couple that with built in engineering controls and suddenly the need to switch between tools goes away.
No more waiting, parallelize your code
Why wait for code blocks to execute one after the other? Instead, parallelize as many code blocks as you want and never get slowed down.
No language limitations
Use Python, R, SQL and Markdown interchangeably on the same canvas. Our underlying architecture also means there is no limit to other languages we can add to this group.
Deploy on your terms
Zerve simplifies deployment. Deploy in Zerve or handover over to the team in the format that they need. No more friction and no more recoding. Simple.
We’re excitied to shoot for the moon and work towards achieving our mission of elevating the impact of data science & AI on the world. To do that, we have rebuilt the foundations from the ground up and are super excited to share this with the Product Hunt community today!
Ready to try Zerve yourself for FREE?? Signup here today at app.zerve.ai.
We would absolutely love to hear what you think, so please feel free to drop a comment below or reach out to me directly at greg@zerve.ai.
PS. Thank you to @chrismessina for the fantastic advice and guidance as well as hunting our product!
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@greg_michaelson UpVoted 🙌 and Congratulations on your Launch team 🎉
@chrismessina@mohammed_mustafa_jafer Well, the main issue is that there's no data science development environment that gives you both stability and interactivity!
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@greg_michaelson Hi, we create Web Operating System with own app store, where users get software from. Your app is amazing and we want to enable you to share it to our users 🙂 Can we talk?
Zerve arrives just in time to give data science and ML teams a collaborative, iterative environment to develop data science and AI projects, with the ability to quickly pivot into producing delivery deployment-ready code, that can be deployed to AWS or downloaded directly.
You've got to the check this out. This is a hidden gem.
It's been an awesome journey to here, we've interviewed 100s of code-first data users and we would not be here if it wasn't for how generous the community was in helping to guide our product vision. Excited to hear even more feedback and grow our community further.
Building Zerve from the ground up for the last two years has been a wild ride! I am super proud of the work our team has done and there is some really interesting underlying tech in Zerve so if anyone wants to chat about it, comment below!
From scratching the surface of the idea to finally launching the product, saying its been a wild ride would be an understatement. The journey has been highly fulfilling as we as coder try to address the problems we have faced with notebooks all our life's. Focusing on code first data users and solving the challenges they face has been a very rewarding journey.
You can now easily collaborate, share environments and work on multiple streams without having to worry about having a shared kernel which can result in values being ambiguous.
I am extremely proud of the fact I am part of the team behind Zerve. We have given it our all to ensure we come up with a product that solve real life pain points and can help developer and data explorers achieve their task in a much better way
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