Zerve AI

Data notebooks haven't changed in over a decade. So we rebuilt them from scratch. Zerve brings together the notebook flow you know with agentic execution, reproducible canvases, and real cloud compute, all designed around how data teams actually work. Join founders Greg Michaelson, Phily Hayes, and Jason Hillary for a live demo. You'll see: • Improved stability, collaboration, and speed • Faster workflows and smoother iteration • Design decisions and what's coming next

Cursor and Windsurf are terrible for Data Science. There. I said it. You write a 500-word prompt begging it to understand your data. Cross your fingers it remembers which column is which. Watch it hallucinate insights from thin air. After 3 weeks testing Zerve, I finally understand why data scientists are jumping ship. 🎯 The Dirty Secret of AI Coding Tools Cursor/Windsurf assume your data lives in your head: • You describe schemas like writing a novel • The LLM forgets your context every 5 messages • Real messy data breaks everything • You debug hallucinations, not logic Zerve knows data lives in the real world: • Your data loads instantly, visible in cells • Each transformation shows live results • Context persists because it's NOT in a prompt • You debug actual data, not LLM confusion 📊 What Actually Happens Yesterday I threw a messy CSV at both tools. In Cursor: Spent 20 minutes describing my data structure. "Column 3 is dates, column 7 has missing values..." LLM still mixed up my columns. Had to restart 3 times. In Zerve: Typed "Explore my Real World Data.csv" 30 seconds later: ✓ Loaded 2M rows with correct types ✓ Found 12% missing values I didn't know about ✓ Caught duplicate rows from bad joins ✓ Built complete EDA pipeline All visible. All editable. All working. Video proof below – Plus link to try it yourself 👇 🔄 The moment I switched: While I was still teaching Cursor what a datetime was, Zerve AI had already found data leakage between my train/test splits. Who else is done writing dissertations about their datasets? ♻️ Repost to save a data scientist from prompt engineering hell

Last week, I was working on a small ML workflow. Just a simple one - few scripts, few datasets, a couple of experiments. But by the time I moved from notebook to code cleanup to deployment… I had 7 tabs open, 3 environments broken, and zero patience left. 😅 It hit me that building isn’t always the hard part - it’s managing the mess around it. That’s when I stumbled upon something called Zerve AI. It doesn’t feel like a “new tool.” It feels like the platform every data person secretly wished existed. You write your logic once, and it can turn into an app or an API instantly. You want to scale it? Just tell it, and it spreads the workload across machines like magic. You get stuck? There’s an agent that actually understands your context and helps fix things inside your workspace. For the first time, I didn’t feel like I was wrestling with my own workflow. It just worked. Zerve AI takes care of the heavy stuff - deployment, orchestration, scaling - so you can actually focus on the part that matters: building. Feels like someone finally understood the pain of every data scientist and just decided to fix it. If you’ve ever felt buried under broken scripts, endless debugging, and 10 open terminals — you’ll get why this feels like a breath of fresh air. 🔗 Check it out here: https://hubs.la/Q03NFl6N0 Have you ever come across a tool that instantly made your workflow feel easier? #DataScience #Zerve #MLOps #Workflows #Productivity #AI

It took me days to solve Titanic dataset when I started with DS. Yesterday, I watched an AI agent solve it in under 2 minutes. No coding. No debugging. Just prompts. I created a video to show you that 😇 Here's what happened: → Planned the entire data science pipeline → Cleaned and prepared the data automatically → Engineered features (titles, family sizes, missing values) → Created visualizations to understand patterns → Tested 5+ classification models → Compared performance and picked the best one → Did hyperparameter tuning All through natural language prompts. The best part? You see the code. You can edit it. It's not a black box. That's Zerve AI - I used free credits to try it out! You must check as well. Here is the link: https://hubs.la/Q03Nl3Kt0 Watch how it works ↓ --- ♻️ Repost to help other builders 💚 ➕ Join 27.000+ AI/ML builders here: https://lnkd.in/ds_SzEUH

We’re going live to see how far we can get building three real data projects in an hour, with AI helping along the way. No perfect scripts or polished demos — just curiosity, problem-solving, and a team trying things in the open. Join us, learn with us, and see what realistic, human, AI-powered data work looks like in real time.

Go from data to insights, APIs and apps in minutes with Zerve, the modern dev environment for data work. Collaborate with agents designed for data.