Zerve is the agentic data workspace designed for anyone who works with data, from solo analysts, data scientists and business users alike. Zerve brings together exploration, advanced analysis, collaboration, and production deployment into a single AI-native environment, so that important data work doesn’t stall, break, or disappear.
Zerve is used by data professionals in companies such as BBC, QVC, Dun & Bradstreet, Airbus, Canal+, S&P Global, and many others.
Zerve makes advanced data work accessible, durable, and deployable from day one, starting with the messy, real-world data most projects begin with.
At the heart of Zerve is a new way for humans and AI agents to work together. Zerve’s AI agents understand the full context of a project and actively help plan, build, debug, and iterate across multi-step analyses.
Agents can assist with tasks like cleaning and transforming data, identifying issues, and testing approaches, reducing the manual effort that slows teams down. This means working at a higher level of abstraction without being slowed by setup or syntax. With Zerve, you always have an expert data scientist at your side, guiding decisions, suggesting next steps, and taking action.
Zerve also supports real-time human collaboration in the same shared environment, making it easy for individuals, teams, and business stakeholders to work from the same context without translation layers or hand-offs.
Unlike traditional data notebooks, workflows in Zerve are reproducible and stable even as they become more complex. Users can work across Python, SQL, and R in a single workspace, connect directly to databases, data lakes, and warehouses, and integrate with Git for version control.
The built-in distributed computing engine powers massively parallel execution for large-scale analysis, simulations, and AI workloads, with multi-agent orchestration coordinating complex pipelines behind the scenes.
Zerve can be used as SaaS, self-hosted, or even on-premise for highly regulated environments. The result is simple but powerful: every analysis built in Zerve can be deployed instantly as an app, API, or scheduled job, ensuring that data work reaches real users, systems, and decisions.
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Overview by
Rebecca Steinberg Herson
