Every enterprise is sitting on a big mountain of data that it cannot fully visualize, especially when doing it manually. Everything from customer records, payment details, to employee files and more, the PII and PCI data accumulates across databases, data warehouses, and cloud pipelines faster than any compliance team can manually track it.
Manual auditing of the entire data isn't reliable and scalable. Doing it manually can lead to Spreadsheet-driven reviews, missed columns, misclassifying fields, and audit trails that collapse under regulatory scrutiny.
DynaTech's AI-Powered PII/PCI Data Detection system addresses this directly, scanning data assets intelligently, tagging sensitive columns automatically, and delivering compliance-grade visibility without turning your data team into a full-time audit department.
Microsoft Copilot embedded across Microsoft 365 and Teams is a productivity layer, and you are already using it to summarize documents, draft messages, and navigate content you already have access to.
Copilot cannot scan Azure SQL databases to fill columns; it carries no concept of your regulatory classification rules unless you build that in separately, and that is a resource-intensive process with no guarantee of coverage consistency.
DynaTech's PII/PCI Data Detection solution operates at the data layer and is powered by multiple technologies and tools, including;
DynaTech's regulations PII data protection system scans your data assets and evaluates columns against configured PII and PCI definitions, including;
Moreover, columns and fields that are mislabeled, unnamed, or carry no governance tags are surfaced alongside correctly labeled ones.
Detected columns are tagged against applicable regulatory frameworks, like GDPR, CCPA, and PCI DSS, without anyone manually reviewing individual tables or schemas.
The AI-powered data management solution flags sensitive data assets, but there's a lack of proper governance controls, and it exposes compliance gaps before they become regulatory issues, giving your team enough time to act.
Classification logic is configured against the specific column-level definitions as per the different regulations and frameworks like GDPR, CCPA, and HIPAA, etc. Audit evidence is tied directly to regulatory standards, not generic data labels that require reinterpretation later.
Data detection and analysis outputs are fed into structured compliance reports, clearly listing out;
These tasks don't require manual assembly by your governance team, as the automated PII PCI detection system takes control.
Microsoft Purview integration provides lineage visibility, sharing information like;
Compliance teams get a traceable data flow map, not a static column inventory.
All types of data, including sensitive information, do not stay where they were originally stored and move through ETL pipelines, land in staging tables, get copied into reporting environments, and end up in different places, sometimes in areas no one has accounted for during system design.
Compliance teams inherit this data estate and are asked to audit, but where manual classification takes weeks, even small errors like missed columns can lead to varied results. Moreover, the results also differ as per the auditor, as different people work on the auditing part.
When a regulator asks where cardholder data lives across your environment, a partially complete spreadsheet is not a defensible answer. The problem is not intent, but the scale of data that's out there to audit, and this is where manual processes fail.
The GDPR CCPA GLBA PCI compliance solution connects to your data environment through configured integration layers and scans different data assets, like;
The scanned data is added to columns that match PII and PCI data profiles. With our solution, multiple smart technologies work together to deliver results.
When you use DynaTech's PCI PII data detection solution, every classification is applied against specific, configured parameters and surfaces data it reads and sees while your governance team decides what to remediate.
A financial services firm runs a compliance scan ahead of a regulatory review. The automated PII PCI detection system scans their data warehouse and delivers dozens of columns containing email addresses, national IDs, and date-of-birth fields carrying no governance tags. Each is classified, labeled, and documented in a structured audit report, giving the compliance team actionable evidence within hours rather than weeks.
Our solution detects credit card number patterns in a staging database that was copied from production months earlier. The exposure is flagged with column-level detail and environment location, routed to the data engineering team, before the next PCI DSS audit cycle opens.
A data pipeline ingests customer records from a CRM integration layer, and the regulations PII data protection system identifies PII columns in the pipeline's output table and traces their lineage back to the source through Microsoft Purview, giving the compliance team a documented data flow map tied directly to CCPA requirements.
| Business Challenge | Agentic AI Solution |
| Sensitive data is scattered across the organizational data storage system and servers with no centralized inventory. | The AI solution we have built scans connected data assets and builds a classified inventory of PII and PCI columns without manual schema review. |
| Manual compliance auditing is error-prone and inconsistent as auditors change, and doing this at scale is time and resource-intensive. | Automated classification applies configured regulatory definitions consistently across every table and schema, eliminating auditor variance, and it takes less time. |
| Undiscovered sensitive data exposure creates a risk of regulatory violations, exposing the organization to legal and regulatory issues. | Risk detection surfaces untagged or ungoverned columns before audit cycles, and this gives your compliance teams time to remediate the errors rather than react. |
| Compliance reports require weeks of manual assembly, and with high volumes of data and limited time, this causes issues. | Structured audit reports are generated automatically from detection results, aligned to GDPR, CCPA, and PCI DSS documentation standards. |
| Lineage gaps prevent compliance teams from tracing sensitive data flows and make identifying the difference between PII and PCI data difficult. | Microsoft Purview integration maps where PII and PCI data originates, how it moves through pipelines, and where it ends up, while adding each aspect of data to the right columns, while following data protection regulations. |
| PCI/PII data in non-production environments goes undetected. | The system scans across environments, not just production, flagging sensitive data wherever it has spread. |
The solution to AI detect redact PII PCI at scale operates across clearly separated layers, including;
Want to know more about how the detection system works?
Our team deploys the AI-enabled solution to align with your existing Microsoft Fabric and Purview environment, and the setup of the entire system covers;
In this entire schema of configuration, we don't need to make any data schema changes. Moreover, scan scope, classification definitions, and regulatory mapping are configured during the onboarding phase based on your data environment and compliance obligations without altering source systems and disrupting live pipelines.
Your next compliance audit either finds sensitive data your team missed or it doesn't, and in both the ways, you win. After deploying DynaTech's PII/PCI Data Detection system, your organization knows exactly where sensitive data lives, and now it's classified, tagged, and traceable across every connected data asset.