Agentic AI
AI Data Quality Agent
An autonomous agent that detects, explains, and remediates data issues.
Architecture diagram placeholder
Add one at /public/images/projects/ai-data-quality-agent.png
The Challenge
Data quality issues were caught late — usually by the business, after bad numbers had already shipped to executives.
The Solution
Built an agentic system that continuously profiles pipelines, reasons about anomalies with an LLM, files enriched tickets with root-cause hypotheses, and proposes fixes for human approval.
Key Achievements
- Shifted quality detection left, catching issues before they reached reports
- Reduced mean-time-to-detect for data incidents dramatically
- Generated human-readable root-cause explanations automatically
Lessons Learned
The value of an AI agent is in the guardrails: constrained tools, human approval on writes, and full observability make autonomy safe.
Let's build something intelligent together.
Whether you're modernising a data platform or bringing agentic AI into production, I'd love to hear what you're working on.