Data is your organization's most valuable asset, and most significant liability. ARLITECH's data protection services help you secure, govern and comply with confidence.
Automated discovery of sensitive data across your environment (structured, unstructured, cloud and on-premise) with risk-based classification.
DLP policy design and enforcement across email, endpoints, web and cloud channels preventing unauthorized data exfiltration.
End-to-end encryption solutions for data at rest, in transit and in use, with enterprise key management and HSM integration.
GDPR gap assessments, data mapping, privacy impact assessments (DPIA) and documentation to support regulatory compliance.
Immutable backup strategies and tested recovery procedures protecting against ransomware and ensuring business continuity.
PAM solutions controlling and auditing access to sensitive systems and data by privileged users, admins and service accounts.
Our data protection services are designed from the ground up to meet the requirements of GDPR, NIS2, ISO 27001 and industry-specific regulations, so compliance is a byproduct of good security, not an afterthought.
Get Expert GuidanceTechnical and organizational measures for appropriate data security.
Data protection controls aligned with NIS2 risk management obligations.
Information classification and handling controls per ISO 27001 requirements.
Data protection records and evidence packages ready for regulatory audits.
Data protection is simultaneously a technical and an organisational question. In practice most organisations produce the policies but do not know where their sensitive data actually sits. The work therefore starts with discovery.
Automated discovery across the environment: file shares, databases, cloud storage, mailboxes. The aim is establishing where sensitive data sits and in what volume.
Where it comes from, where it is stored, who it passes to. Without a data map neither access management nor incident response can be planned.
Access restriction, encryption at rest and in transit, logging, data loss prevention. Built on existing tool capabilities wherever possible.
Data is created continuously, so discovery must be too. Regular access reviews and enforcement of retention periods.
Data protection controls do not stand alone: each answers a specific risk and each also satisfies a compliance obligation.
| Control | Which risk it answers | Related requirement |
|---|---|---|
| Discovery and classification | We do not know where sensitive data is | GDPR Article 30, ISO 27001 A.5.12 |
| Access restriction | Too many people see what they do not need | GDPR Article 32, ISO 27001 A.5.15 |
| Encryption at rest | Loss of a disk or backup | GDPR Article 32, ISO 27001 A.8.24 |
| Encryption in transit | Interception, man in the middle | ISO 27001 A.8.24, NIS2 measure 8 |
| Logging | Cannot reconstruct who saw what | ISO 27001 A.8.15, GDPR accountability |
| DLP | Data leaving by email or to cloud | GDPR Article 32 |
| Retention regime | Unnecessarily retained old data | GDPR Article 5(1)(e) |
| Anonymisation | Test and development environments | GDPR Article 25, privacy by design |
Through automated discovery. In our experience every organisation has surprises: spreadsheets containing personal data on file shares, old exports in the development environment, customer data in a cloud service IT does not know about. Discovery covers both structured and unstructured data and gives a quantitative picture, not just a list.
No. They are necessary, but both the authority and an incident look at operation: is access genuinely restricted, are backups encrypted, is data deleted when retention expires. A document remains paper regardless of who signed it. The quickest check: look at how many people have access to the HR folder, and how many can actually justify it.
In a personal data breach the supervisory authority must be notified within 72 hours where the breach poses a risk to data subjects. The clock starts from becoming aware, not from complete investigation. It is therefore worth preparing the notification template in advance and deciding who makes the call, because an incident starting at a weekend leaves no time for that.
This is one of the most common gaps. A copy of the production database frequently lands in a development environment where access is looser and protection weaker. The answer is anonymisation or pseudonymisation: the structure survives, the personal data does not. This is the practical implementation of privacy by design, and in most cases it can be automated.