Zerve

What does Zerve do?

Zerve's agent maps your warehouse, learns the schema, and turns that context into notebooks, reports, and deployable outputs. Data Discovery scans the full dataset and infers relationships before analysis starts; Agentic Notebooks then let you write, run, and version AI-assisted work while compute scales in parallel. Conversational Reports pull results from notebooks into stakeholder-ready narratives, and Deployments ship apps or APIs from the same workflow without rebuilding pipelines. At scale, Zerve says discovery runs on billions of rows with no sampling and completes in 2, 4 minutes. The platform is built for collaborative, production-grade execution, with reusable environments, Git-native workflows, and persistent institutional knowledge so later analyses build on earlier ones. It can run in SaaS, self-hosted, or on-premises modes, and the enterprise setup supports zero external traffic. Customers shown on the site include NASA, BBC, Airbus, and S&P Global.

Why use Zerve?

• It combines discovery, analysis, reporting, and deployment in one workflow, so teams can keep context instead of moving between tools.
• The platform can scan full warehouses and infer relationships before analysis, which reduces manual schema hunting.
• Parallel compute and reusable environments let multiple analyses run at once without sacrificing reproducibility.
• Self-hosted, on-premises, and air-gapped options give teams control over where compute runs and where data flows.
• Institutional knowledge persists across analyses, so later work can build on prior investigations instead of starting over.

Who is Zerve for?

• Data scientists who need reproducible, AI-assisted notebooks that can scale compute automatically.
• Data analysts who want to turn analysis into stakeholder-ready reports without rebuilding work.
• Analytics engineers who need deployable apps or APIs from notebook outputs.
• IT and data owners who want warehouse discovery before teams start querying.
• Security-conscious enterprises that need self-hosted or on-premises control over data and models.

What are Zerve's key features?

What does Zerve integrate with?

• Slack
• BigQuery
• Snowflake
• Redshift
• S3
• AWS
• Streamlit
• FastAPI
• Google Cloud
• Azure
• PostgreSQL
• OpenAI
• Anthropic
• AWS Bedrock
• Azure OpenAI
• Okta
• Azure AD
• Google Workspace

What are Zerve's use cases?

How does Zerve work?

1. Connect your first data source through Deep Data Integrations, then use Data Discovery to inspect tables, relationships, and available warehouse context before analysis begins.
2. Open Agentic Notebooks and start building with agents, reusable environments, and Your Packages, Your Environment so work stays reproducible as the analysis grows.
3. Refine findings into Conversational Reports or Reports, using collaboration features to shape a single polished report that stakeholders can review without rebuilding the notebook.
4. Publish the result with Deployments or the Zerve API, turning notebook output into an app or API that can be reused by other teams.
5. Set governance with Self-hosted, SSO / SAML, RBAC, and Audit logs, then keep Institutional Knowledge inside the workspace as projects evolve.

How much does Zerve cost?

Frequently asked questions