Unified Data Quality & Observability Meets Enterprise Scale
Poor data quality remains the primary barrier to the adoption of trusted AI. Inconsistent, incomplete, and siloed data reduce model accuracy and increase operational risk. Lack of standardized definitions, lineage, and validation rules leads to unreliable insights and governance gaps. Without automated DQ monitoring and remediation, AI initiatives struggle to scale and deliver real business value.
DQLabs is an AI-powered data quality and observability platform that helps organizations ensure reliable, trustworthy, and real-time data across the enterprise. By leveraging advanced AI/ML and generative AI, DQLabs automates quality monitoring, anomaly detection, root cause analysis, lineage tracking, and remediation at scale, without requiring extensive coding.
With modules spanning Data Cataloging, Quality Scoring, Observability, and Master Data Management, DQLabs unifies data health in a single platform that integrates seamlessly with modern cloud, BI, and workflow ecosystems.
YASH Technologies and DQLabs have partnered to redefine enterprise data excellence. Together, we combine YASH’s proven expertise in large-scale data platform modernization, governance, and advanced analytics with DQLabs’ cutting-edge AI-powered observability and quality automation platform.
This collaboration provides a trusted, intelligent, and scalable data foundation, enabling organizations to accelerate transformation, enhance decision-making, and achieve AI/ML readiness.
