High Data Quality is the most critical factor in determining the success and safety of any artificial intelligence deployment. Yahyou provides specialized auditing and enhancement services to ensure your datasets are accurate, complete, and representative of real-world scenarios. As the AI Governance Pioneer in Pakistan with certified global operations, we bridge the gap between raw information and actionable intelligence, ensuring your models are built on a foundation of integrity across the USA, UAE, and Europe.
Traditional data management is insufficient for probabilistic AI systems. Independent Data Quality assessments specifically address the unique risks associated with machine learning—such as bias, hallucination, and model drift caused by "noisy" data. Failure to verify these aspects can result in massive operational failures and significant reputational damage.
We specifically test for Data Accuracy (verifying truthfulness), Completeness (ensuring no missing critical variables), and Consistency (maintaining uniform standards across datasets)
Providing evidence that your training data adheres to the strictest global guidelines, such as the EU AI Act’s requirements for high-quality datasets.
Verifying adherence to internal ethical policies and international data standards to prevent automated discrimination.
Our methodology is designed to be comprehensive and repeatable, ensuring consistency across different model types and data environments. This structured approach accelerates the assurance process while maintaining high technical rigor.
We review your existing data architecture and documentation to confirm how data is ingested and controlled before technical testing begins.
This is the deep technical dive. We test the data's distribution, validity, and uniqueness against pre-defined thresholds to ensure statistical validity.
We validate data provenance (origin) and pipeline integrity. We also confirm that the data is resilient against poisoning attacks and meets privacy standards.
We issue a formal Data Quality report, including a final health score, identified anomalies, and a clear, actionable roadmap for data purification.
Our deliverables provide the definitive evidence you need for internal reporting and external regulatory defense. We ensure all documents are audit-ready and legally sound.
A detailed document confirming the testing methodology, findings, and overall quality score.
Specific technical recommendations to cleanse identified data errors or gaps.
Mapping all findings against relevant mandates (e.g., EU AI Act data requirements, regional laws in Pakistan, USA, and UAE).
Prioritized actions required to achieve full data assurance.
A plan for ongoing internal data observability to prevent "data drift" over time.
Data Governance is the framework of rules and roles; Data Quality is the technical measurement of the data itself. You need both to ensure AI safety.
Yes. Detecting bias in data distribution is a core component of every Data Quality engagement to ensure your AI doesn't produce unfair outcomes.
We cover global standards including the NIST AI RMF, the EU AI Act’s data provisions, and ISO/IEC 25012 standards.
For high-risk models with frequent data updates, we recommend an audit every 6 months to ensure the "ground truth" hasn't shifted.
Don’t risk reputational or legal exposure due to flawed data. Partner with the experts to get the objective proof you need for trustworthy AI.
