Semantic context, not guesswork
Map business concepts to governed metrics, dimensions, and joins. Reduce ambiguity and keep analytics consistent across teams.
Turn questions into governed SQL — built for enterprise analytics.
2-SQL helps analytics and data platform teams translate natural language into warehouse-ready SQL with the guardrails enterprises demand: semantic context, access controls, auditability, and predictable performance.
Access-aware query generation
Designed for enterprise permission models and least-privilege analytics. Keep data access aligned with policy and role-based controls.
Auditable outputs
Generate SQL that supports review workflows: explainable intent, traceable transformations, and change-friendly patterns for governed analytics.
Warehouse-ready execution
Produce SQL optimized for modern warehouses and lakehouses (Snowflake/BigQuery/Databricks-style workloads), with performance-aware patterns and predictable cost posture.
Example
Natural language → governed SQL (illustrative)
Question:
"Show weekly net revenue by region for enterprise customers, last 12 weeks."
Generated SQL:
SELECT
DATE_TRUNC('week', order_date) AS week,
region,
SUM(net_revenue) AS net_revenue
FROM analytics.orders
WHERE customer_segment = 'Enterprise'
AND order_date >= CURRENT_DATE - INTERVAL '12 week'
GROUP BY 1, 2
ORDER BY 1 ASC;FAQ
Is this a chatbot?
No. 2-SQL is positioned as an enterprise analytics capability — translating intent into SQL with governance, consistency, and operational controls in mind.
What’s the deployment model?
Early stage. The goal is to support enterprise-ready deployment options and security requirements.
Request access
Email: hello@2-sql.com
(If you don’t have email routing set up yet, we can swap this to a form later.)