Vibe code your data context
or try Rig's managed solution
Claude Code lets you vibe code your data context from scratch. Rig builds it for you and keeps it fresh as your schema changes.
Can you vibe code your data context?
Yes. Claude Code is an agentic coding tool that lives in your terminal. It reads your codebase, edits files, runs commands, and ships. It suits engineers who want to build custom things. Shipping the first version of a vibe coded feature is easy, but building systems that understand and maintain data context is hard, and Rig builds and maintains that context.
Already using Claude Code? Connect Rig via MCP and give it business context that understands your data, with sandbox validation and RBAC built in. See how Rig MCP works
Maintaining context in Claude means that you'll need to:
- →Manually define semantic relationships between tables
- →Encode business logic and metric definitions your model can reason over
- →Build and tune agent orchestration so queries don't spiral into nonsense
- →Implement confidence scoring so you know when to trust the output
- →Stand up query sandboxing, RBAC, and audit logging yourself
- →Write warehouse connectors for every source
- →Keep documentation in sync as things drift
- →Do all of it again next quarter when your data model evolves
Why teams choose Rig instead
Business context that builds itself from your schema without manual mapping
Automatically detects schema drift, from dropped columns to new enum values, and auto-updates so the context never goes stale
Build automations that close the loop: update your CRM, trigger Slack alerts, generate board-ready reports
Enterprise-grade governance from day one: sandboxed queries, role-based-access-control, and a full audit trail
Reliable data for anyone on your team in their existing AI tools like Claude Code
How they compare
A feature-by-feature breakdown of Rig vs. Claude Code for building and maintaining data context.
| Feature | Rig | Vibe coded (with Claude Code) |
|---|---|---|
| Setup | Connect your warehouse, let Rig Map build, then start asking questions | Build a text-to-SQL pipeline, prompt layer, and semantic model from scratch, and then maintain it |
| Governance | Built-in sandbox, audit trail, and permissions so users and agents only access the data they are allowed to from day one | Design and enforce query sandboxing, permission scoping, and audit logging yourself, across every agent, user, and endpoint |
| Keeping context current | Rig Map detects schema drift and updates itself when your warehouse changes | For every schema change, someone needs to catch it, fix the mappings, and re-validate for every sprint, indefinitely |
| Data Agents | Orchestrator + MCP + >300 integrations, production-ready on day one | Build orchestration, routing, retries, and tool integrations from scratch and then debug when they interact in production |
| Automations | Answers trigger reports, alerts, CRM updates and workflows automatically | Wire up every downstream action manually (Slack alerts, CRM writes, report generation) and maintain each integration as APIs change |
| Time to value | Live in days, no dedicated headcount | A three to six month build, plus a data team to maintain it |