AI Powered Data Quality Assistant

DQA Orchestrate is an AI-powered Data Quality Assurance system designed to make data reliability fast, consistent, and collaborative. Built on IBM watsonx Orchestrate, it wraps a chat-first agent around a modular toolkit for profiling datasets, generating validation rules with AI, and running automated checks. A human-in-the-loop approval step ensures governance: the agent proposes rules, reviewers approve or refine them, and then validations execute at scale. When issues are found, the flow can create tickets automatically and feed insights to quality monitoring and drift detection, enabling continuous improvement. Technically, the project provides a lightweight FastAPI server (localhost:8000) with clear OpenAPI specs, plus standalone tools (Profiler, Rule Generator, Validator) that can be invoked by the Orchestrate agent. The Quick Start guides you through environment setup, running the API, and testing tools and unit tests for confidence. The architecture emphasizes extensibility: add new checks as modules, connect to different data sources, and plug into workflow systems for ticketing. Designed for hackathon speed yet production-minded, DQA Orchestrate demonstrates how an AI agent can operationalize data quality—reducing manual effort, increasing coverage, and providing auditable, repeatable checks with human oversight and actionable remediation.