2Sequel is an enterprise-grade platform that translates natural language into precise SQL queries for Postgres, MySQL, and SQL Server—giving every team member direct, secure access to business data without writing a single line of code.
By grounding queries in company-specific metadata and applying strict field-level security controls, 2Sequel delivers the accuracy, auditability, and governance that enterprise data teams require.
Live translation
Natural language input
“Show me total revenue by region for last quarter”
Generated SQL
SELECT region, SUM(revenue) AS total FROM sales WHERE quarter = CURRENT_QUARTER - 1 GROUP BY region ORDER BY total DESC;
Adaptive output
Top region: North Europe — €2.4M (+18% vs prev quarter)
Non-technical users—from CEOs to product managers—query any connected database using plain language, eliminating dependency on engineering teams for routine data requests.
Field-level access controls, native data masking, and strict authorization boundaries prevent prompt injection and keep every query within approved governance boundaries.
Grounded in company-specific metadata, business glossaries, and semantic layers, 2Sequel achieves the high accuracy enterprise decision-making demands—far beyond generic LLM SQL generation.
The user asks a conversational question. The model extracts latent semantics, isolating business metrics, geographies, time filters, and groupings from natural-language input.
2Sequel synthesizes a native query optimized for the target database—Postgres, MySQL, or SQL Server—respecting schema structure and field-level authorization rules.
The system interacts directly with the data infrastructure within strict security boundaries, eliminating human intermediaries from the retrieval loop entirely.
Unlike legacy systems that return raw tables, 2Sequel adapts the response: counters, averages, rankings, sorted lists, or ready-to-use summaries—context-matched to the original question.
CEO · CMO · Product Manager · Financial Analyst
Ask any data question in plain language. No SQL knowledge required, no wait for an analyst, no static dashboard limitations. Direct answers to ad hoc business questions, instantly.
CTO · Data Engineer · CISO
Reduce the volume of routine query requests. Maintain full governance through field-level controls, data masking, and audit trails. Replace manual SQL bottlenecks without sacrificing security posture.
Database Compatibility
2Sequel connects natively to the most widely used relational database engines in enterprise environments, requiring no schema changes or additional data pipelines.
Security & Compliance
Field-level access controls, native data masking, and strict authorization boundaries prevent prompt injection and keep every query within approved governance boundaries.
Field-level access controls per user role
Native data masking for sensitive columns
Explainable query tracing & audit trail
What previously required a data request, analyst assignment, SQL writing, and formatted report now happens in a single conversational turn.
Security is not an add-on. Field-level masking, access boundaries, and explainable query tracing are architectural features, not configuration options.
Every business user becomes self-sufficient in data retrieval, freeing engineering teams from the human API bottleneck that slows most analytics workflows.
FAQ
Practical answers on accuracy, security, compatibility, and what makes 2Sequel different from other Text-to-SQL and BI tools.
2Sequel achieves enterprise-grade accuracy by grounding the LLM in company-specific metadata, business glossaries, and semantic layers. Unlike generic models that rely on raw schema analysis, this context-enriched approach dramatically reduces ambiguity and malformed queries.
Every query operates within strict authorization boundaries. Field-level access controls determine which tables and columns are accessible per user role. Prompt injection attempts are isolated architecturally, and the system never generates destructive or unauthorized operations.
2Sequel natively supports PostgreSQL, MySQL, and SQL Server—the three dominant relational database engines in enterprise environments. Connection requires no schema changes and no additional data pipelines.
Open-source Text-to-SQL tools often expose credentials through local protocols, lack field-level governance, and produce inconsistent results on complex schemas. 2Sequel is built for enterprise accountability: native data masking, auditable query tracing, and a RAG architecture grounded in company metadata.
DevOP case study
An enterprise text-to-SQL interface designed to make data queryable without giving up control or auditability.
DevOP role
LLM-flow architecture, metadata grounding, authorization controls, query UX, and query tracing.
Let non-technical roles query company databases without creating unauthorized or opaque queries.
The same design supports data copilots and internal assistants operating within controlled permissions and sources.