Features
AI agent for data analysis that learns your data context
Multi-language notebook (Python, SQL, R, GraphQL)
Git-native versioning with two-way sync
Parallel and scalable cloud execution
One-click deployments to APIs, apps, dashboards
Scheduled jobs and pipelines
Conversational reports for stakeholders
Automatic data warehouse discovery (schema, lineage, quality)
Institutional knowledge persistence across projects
BYOK (bring your own API keys) for AI models (OpenAI, Anthropic)
Self-hosting via AWS CloudFormation templates
On-premise air-gapped deployment (Enterprise)
Credit-based usage system (Zerve credits)
Referral and publishing rewards (earn credits)
Collaborative editing with real-time agent assistance
Live knowledge graph from code, commits, issues, and docs
Feasibility analysis: flags buildable vs risky items
Technical design document generation grounded in service topology
Impact assessment maps services, APIs, and dependencies across repos
Auto-scoping epics into Jira/Linear stories with effort estimates
One-shot production code generation grounded in service patterns
AI code reviews with cross-repo impact analysis
Production issue triage via MCP
Conversational learning from Slack and Jira
Accelerated onboarding via system-level Q&A in coding agents
Create Jira tickets and merge requests from Slack
MCP server for integration with Cursor, Claude Code, Codex
On-prem or cloud deployment
No code storage or model training
