Rig vs. the alternatives

    Your data has answers.
    Most tools can't ask the question.

    BI tools show graphs. Search agents summarise documents. Automation tools move data. Rig deeply understands your complex structured data, and lets you build agents that take action with it.

    Data Agent Platform

    Build autonomous agents that understand complex internal data. From fraud investigations to churn prevention to revenue ops.

    Auto-Generated Context

    Our FDE agent builds and maintains rich data context automatically. No endless definitions — schemas stay current as your warehouse evolves.

    Governed Sandbox

    Every query runs through our orchestrator sandbox. Auditable SQL, permission-aware execution, reduced warehouse bills.

    Question to Action

    Go beyond dashboards. Data Agents write reports, draft outreach, create CRM deals, and push to 300+ integrated tools.

    Third-Party Agent Ready

    Connect Claude, GPT, or any AI via MCP. Your context layer and orchestrator serve any agent that needs your data.

    Weeks, Not Quarters

    Connect your warehouse and start building Data Agents immediately. No six-month implementation or army of consultants.

    Head-to-head

    How Rig stacks up against tools you might be evaluating.

    Approach
    Connect your warehouse and go
    Build and maintain a bespoke data-query stack
    Governance
    Built-in sandbox, audit trail, and permissions
    Implement your own guardrails
    Maintenance
    Semantic layer auto-adapts to schema drift
    Schema changes mean code changes
    Agents
    Orchestrator + MCP + >300 integrations out of the box
    Build agent logic from scratch
    Actionability
    Insights trigger reports, alerts, CRM updates, and workflows automatically
    You build the action layer yourself

    Claude Code helps you build anything. Rig gives you the data intelligence platform so you don't have to.Read more →

    Scope
    Any warehouse, database, or API
    Snowflake data only
    Lock-in
    Warehouse-agnostic — connect anything
    Snowflake-native, requires Snowflake Cortex
    Intelligence
    Multi-step reasoning with orchestrator and context layer
    NL-to-SQL with semantic model
    Actions
    Reports, alerts, CRM updates, and 300+ integrations
    Query results only
    Actionability
    Agents drive downstream actions: emails, deals, escalations, and more
    Returns answers — acting on them is manual
    Scope
    Any warehouse, any source, unified agents
    Queries inside Databricks only
    Lock-in
    Warehouse-agnostic — connect anything
    Databricks-native, requires Unity Catalog
    Output
    Answers, reports, alerts, and autonomous actions
    Answers and visualizations
    Agents
    Full orchestrator with multi-step reasoning
    No agent framework
    Actionability
    Agents trigger workflows, push to CRM, send alerts, and drive decisions
    Displays answers and charts — no action layer
    Adoption
    Hours to days to value
    Weeks to months to value
    Audience
    Mid-market teams, growth-stage companies
    Government, defense, large enterprise
    Pricing
    Transparent, accessible pricing
    Custom enterprise contracts ($$)
    Deployment
    Connect your warehouse, validate accuracy via a risk-free POC, and go
    Heavy implementation + dedicated team
    Actionability
    Out-of-the-box actions: reports, alerts, CRM updates, 300+ integrations
    Actions require custom Ontology apps and engineering
    User
    Any team member asking questions
    Developers writing workflow logic
    Approach
    Autonomous reasoning over your data
    Pre-defined triggers and actions
    Intelligence
    Understands what you ask
    Executes what you build
    Flexibility
    Semantic layer adapts to context
    Rigid — breaks when schemas change
    Actionability
    Agents reason over data and choose the right action autonomously
    Executes pre-wired steps — can't decide what to do
    Core job
    Getting insight from data and taking action with it
    Moving data between SaaS apps
    Intelligence
    AI-driven analysis with governed SQL
    Rule-based automation
    Output
    Answers, reports, and data-driven alerts
    Actions triggered across apps
    Overlap
    Makes sense of what's in those systems
    Connects systems together
    Actionability
    Data-driven agents decide when and how to act — not just shuttle records
    Moves data between apps on a schedule
    Data type
    Structured — warehouses, databases, metrics
    Unstructured — docs, wikis, tickets, chat threads
    AI approach
    Data Agents with context layer & orchestrator
    RAG over documents & knowledge bases
    Best at
    Building agents that query, analyze, and act on data
    Finding information across your apps
    Output
    SQL-backed insights, reports, and autonomous actions
    Summarized answers from documents
    Actionability
    Agents act on insights: trigger alerts, update CRM, send reports, and more
    Surfaces information — doesn't drive action

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