Text-to-SQL
Translate natural-language questions into precise, secure SQL queries validated against your semantic dictionary and data context.
DUAL • FACTORY
Get insights by talking directly to your databases
Questions about data, usable answers: analyses, charts, and ready-to-use reports, with controls and traceability in key steps.
Generate dashboards, charts, and ready-to-share reports
Create dynamic dashboards and charts, then produce exportable reports and summaries ready for day-to-day workflows.
Understands complex data schemas
It works with coordinated agents to map data context and run analysis, reducing dependency on deep technical know-how and making data access more direct.
Security layer
Compliance by design
Dual includes governance controls from day one: transparent operations, access policies, and review trails built directly into workflows.
- Access controls: Role-based permissions and segregation policies built into workflows.
- Traceability: End-to-end review trails for every operation.
- Verification: Source-level citations for transparent validation.
- Audit readiness: Reports structured for governance and compliance checks.
How Dual Factory is used
Complex analysis without manual SQL
Natural-language questions become reliable queries, even on complex databases.
Rapid data exploration
New questions get answers immediately, without rewriting queries from scratch.
Less repetitive work
Less time on joins and filters, more time on result interpretation.
Dashboards generated at the right moment
Visualizations are generated when needed, not only those predefined.
Richer reports with less effort
Advanced analysis becomes accessible without increasing technical complexity.
Differences vs traditional solutions
| Feature | Dual Factory | Traditional solutions |
|---|---|---|
Natural-language data access | Enables users to query structured data through natural language, without writing queries or knowing database structures. | Data access requires technical skills or continuous support from specialized teams. |
Controlled and reliable analyses | Generates validated queries aligned with data context, reducing errors, ambiguities, and unreliable results. | Analyses depend on the quality of manually written queries or rigid preconfigured models. |
Verifiability and transparency of analyses | Every analysis is traceable and verifiable: it is always possible to trace back questions, generated queries, transformations, and results. | Reconstructing how an analysis was produced is complex or impossible, especially over time. |
Continuous monitoring and automatic alerts | Enables monitoring of metrics over time and automatic alerts when relevant conditions or thresholds are met. | Monitoring requires manual setup or continuous intervention by technical teams. |
Data governance and security | Respects existing roles, permissions, and policies, ensuring controlled data access and protection of performance and costs. | Direct data access exposes organizations to security, performance, and uncontrolled usage risks. |
Scalability of analysis | Scales across multiple data sources, users, and use cases while maintaining control, consistency, and operational sustainability. | Increasing users, data, or requests creates bottlenecks and dependence on a few specialists. |
From request to approved content, faster
Book a live demo and explore how Factory fits your editorial process.
Frequently Asked Questions