A global commerce platform, processing billions in transactions annually, engaged Akraya to strengthen their enterprise data governance capabilities.
Challenges Faced
This section outlines the core difficulties and pain points the client was experiencing. It provides context on the hurdles that needed to be overcome before achieving the successful outcome.
Critical PII elements including Social Security numbers (SSN), phone numbers, and full names were being misclassified by AI-powered detection tools.
Fragmented Rules Across Legacy & AI Systems
Over 200 regular expression-based rules had been manually developed over years, but newly implemented AI classification systems were overriding or misapplying established rules.
Unstructured Data Governance Gaps
While structured database data was governed through established scanning processes, the explosion of unstructured data - emails, Jira tickets, transcripts, error logs remained ungoverned.
Akraya’s Strategic Solution
We engineered a comprehensive data governance solution spanning structured and unstructured data environments -
Acted as the authoritative validation layer for classification accuracy across structured databases and unstructured communications.
Measurable Outcomes
Operational
2,000+ misclassifications identified and corrected through systematic validation and engineering collaboration.
Financial
$100’s of Million in legal liability avoided by preventing data exposure scenarios that could trigger regulatory fines.
Business
GDPR, Department of Justice, and international privacy requirements satisfied through accurate classification and retention policies.
Conclusion
Akraya transformed client’s data governance capability from fragmented, manually maintained rules into an integrated framework that bridges legacy regex-based systems and modern AI classification.
