# Conduktor

Bad data in, bad AI out. Schema drift, missing fields, and corrupted streams cause hallucinations, compliance failures, and broken models—often before anyone notices.

## The Real Cost

- **Silent failures:** Models drift without alerts
- **Compliance risk:** Bad data triggers regulatory issues
- **Wasted compute:** Retraining on garbage data

## What You'll Learn

- The data quality issues that break AI pipelines
- How to enforce quality at the source, not downstream
- Building reusable data products teams can trust

## Who This Is For

CDOs, platform engineers, and data scientists building real-time AI systems—RAG, LLMs, or real-time decisioning.