SQL Parsers for BigData, built with antlr4.
AI-native test management for QA engineers, SREs, and DevOps teams. From unit tests to chaos experiments: unified in Markdown, validated in SQL. Built for regulated industries where accountability, traceability, and structured evidence are essential.
YAML-first, domain-driven data governance for AI agents — teach agents your business domains, metrics, and rules before they write SQL
A production-grade, schema-aware PostgreSQL MCP server for enterprise AI. Features Zero-Trust SQL validation, multi-tier permissions, and real-time schema introspection for secure, autonomous database operations.
QA portfolio project demonstrating API testing, SQL validation, and Python automation using DummyJSON E-Commerce API, Postman, SQLite, requests, and pytest.
Eval-driven SQL reliability for AI agents — generate, validate, safely execute, and regression-test LLM SQL. MCP + FastAPI gateways, execution-truth evals, CI regression gate.
Professional SQL ETL validation scripts for Data Warehouse QA — Snowflake, Redshift, Oracle | Healthcare, Banking & Hospitality domains
Reproducible evaluation of schema-grounded Text-to-SQL using BIRD Mini-Dev, with schema retrieval, SQL validation, bounded repair, abstention, and read-only SQLite execution.
A new package that helps developers ensure column safety in SQLite queries by analyzing and validating their SQL statements. The package takes a user's SQL query as text input and returns a structured
Aptoria is a self-hosted Laravel application for API QA, endpoint visibility, regression monitoring, release evidence and lightweight security review.
SQL Change Guard is a secure SQL change management tool that analyzes, validates, and deploys SQL scripts with full audit and compliance support.
A standalone data quality/QA project: SQL validation queries + Great Expectations suite on a synthetic timesheet dataset.
Two-stage LLM-based Text-to-SQL framework with schema retrieval, SQL validation, and self-correction.
Comprehensive end-to-end QA Testing Framework for a Student Management System. Features Web UI Automation (Selenium & Pytest using POM), API Testing (Postman), Database Validation (SQL), and enterprise-grade QA documentation (Test Plan, Test Cases, and Tabular Bug Reports).
Deterministic validation layer between a text-to-SQL model and the warehouse. Proves fan-out, metric contract and policy violations from the sqlglot AST against a semantic contract, repairs what it safely can with a diff, and refuses the rest with a reason. 30 of 30 wrong generations caught, 4.56 ms per query. No model API is called.
Manual and functional QA portfolio demonstrating test case design, regression testing, bug reporting, UAT support, SQL/data validation thinking, and end-to-end workflow validation.
Governed, template-based text-to-SQL for manufacturing: pre-approved SQL templates, a multi-rule validator, and full audit logging, exposed via an MCP server and a no-API-key CLI.
End-to-end e-commerce analysis of 100k+ Olist orders using Excel, Power Query, SQL, and Tableau Public.
SQL data validation QA demo with duplicate checks, workflow consistency checks, attendance validation, and report reconciliation.
Airflow + Postgres DQ platform: observability, rule-based monitoring (SQL+JSON), pluggable alerting, Metabase dashboards.
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