The agentic data platform for data scientists.
Zerve's data science agent maps your warehouse, writes and runs your analysis, and deploys the result โ all in one environment, with full context from every prior run.
Data Discovery
Your agent knows your warehouse before you write a single query.
Zerve automatically maps schemas, join paths, and data quality issues across your entire warehouse โ so every analysis starts with full context from day one.
Institutional Memory
The context from your last run is waiting in your next one.
Zerve captures the methodology, decisions, and context behind every analysis and makes it available to every run that follows โ so your team never starts from scratch again.
DAG Notebooks
Every cell its own runtime. Every language in the same workflow.
Zerve notebooks are DAG-based โ no shared state, cached outputs, fully reproducible. SQL, Python, R, and PySpark interoperate natively so your workflow matches your thinking, not your tooling.
Parallel Compute
Parallelize anything with a single function call.
Zerve's spread() function distributes any iterable across parallel compute nodes instantly. Hyperparameter combinations, model variants, data subsets โ run them all simultaneously and gather results when they're done.
One-Click Deploy
Ship models, APIs, and apps without leaving your notebook.
Every Zerve deployment runs in the same reproducible environment as your analysis. Load any model, dataset, or figure with a single import and go live instantly โ APIs, apps, and scheduled jobs, without handing off to engineering.