Kaizen
Autonomous Software Modernization and Quality Engineering for Legacy Systems.
Turn natural language into high-performance SQL queries with schema-aware intelligence.
AI Pro SQL is a sophisticated database management and query generation platform designed for the 2026 data landscape, where rapid iteration and semantic data access are paramount. Built on a proprietary Retrieval-Augmented Generation (RAG) architecture, it leverages Large Language Models (LLMs) specifically fine-tuned on diverse SQL dialects including PostgreSQL, MySQL, Snowflake, and BigQuery. Unlike generic AI assistants, AI Pro SQL indexes your specific database metadata locally or via encrypted cloud tunnels to provide schema-aware query generation, ensuring that table names, joins, and column references are 100% accurate to the user's environment. The 2026 version introduces 'Self-Healing Queries,' which automatically detect and fix syntax or logic errors by testing executions in a sandboxed environment. This tool positions itself as a critical bridge between non-technical stakeholders and complex relational databases, while providing senior DBAs with advanced optimization recommendations and automated documentation. Its security-first approach ensures that actual row-level data never leaves the local environment, sending only structural metadata to the AI engine for query construction, making it suitable for SOC2 and GDPR-compliant organizations.
Uses RAG to inject database-specific DDL and constraints into the LLM prompt window for zero-shot accuracy.
Autonomous Software Modernization and Quality Engineering for Legacy Systems.
Bridge the gap between natural language and complex database architecture with AI-driven query synthesis.
Add AI-powered chat and semantic search to your documentation in minutes.
Automated Technical Documentation and AI-Powered SDK Generation from Source Code
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Analyzes existing legacy SQL to suggest modern optimizations, such as replacing subqueries with CTEs.
Dynamically generates Entity Relationship Diagrams based on metadata and inferred foreign keys.
A proxy layer that scrubs PII from queries before they are sent to the AI processing engine.
Instant translation of code between T-SQL, PL/SQL, and Snowflake-specific syntax.
If a generated query fails, the AI analyzes the error log and auto-retries a corrected version.
Enables users to search through historic queries using intent-based natural language rather than keywords.
Non-technical marketing managers need custom data weekly without waiting for the BI team.
Registry Updated:2/7/2026
An organization is migrating from Oracle to PostgreSQL and needs to rewrite thousands of stored procedures.
A specific dashboard is loading slowly due to unoptimized JOINs.