The Training Data Dilemma
AI teams need data. Regulators demand protection.
Personal and sensitive data embedded in raw datasets
GDPR & EU AI Act restrictions on data usage and purpose limitation
Risk of data persistence and reuse by external AI platforms
Shadow AI and uncontrolled data sharing across teams
The MAYA Approach
Secure Training Data Management by Design
MAYA acts as a secure intermediary layer between enterprise data and AI workflows, ensuring that no identifiable personal data is ever exposed during model training or experimentation.
Data sovereignty remains fully with your organisation
Privacy controls are embedded, not bolted on
AI teams work faster with less risk
How It Works
How MAYA Secures Training Data
01
Data Ingestion
Enterprise training data is securely ingested from internal systems, data lakes, or pipelines without changing existing workflows.
02
Identification & Classification
MAYA automatically detects and classifies personal data, sensitive attributes, and regulated fields across structured and unstructured datasets.
03
Privacy-Enhancing Transformation
Advanced Privacy-Enhancing Technologies (PETs) anonymise, pseudonymise, and transform sensitive data into AI-safe formats while preserving analytical value.
04
AI-Ready Processing
Only sanitised, privacy-safe data is used for AI training, fine-tuning, or testing on-premises or in private/cloud environments.
05
Controlled Enterprise Governance
No data is stored, reused, or retained by external AI providers. All access, context, and governance remain fully under enterprise control.
Use Cases
AI & ML teams preparing training datasets
Data protection officers and compliance leaders
Enterprises operating under GDPR / EU AI Act
Regulated industries (finance, healthcare, public sector)
Ready to Build Responsible AI?
Speak to a Maya expert to see how we can help your team deliver smarter, safer AI with confidence