Protegrity and AWS
Protect Sensitive Data Across Analytics and AI
AWS runs cloud services. Protegrity protects sensitive data everywhere it’s used.
AWS provides the infrastructure for analytics, machine learning, and GenAI. Protegrity adds enterprise data protection—tokenization, encryption, and policy enforcement—so regulated data can be safely used across AWS analytics and AI services without exposure.
Summary
If your AWS environment includes PII, PHI, financial, or regulated data, AWS alone is not enough.
AWS controls infrastructure, identity, and access. Protegrity controls how sensitive data itself is protected and reused. Enterprises use both because:
- AWS does not provide field-level data protection
- AWS security controls do not persist when data moves across services or accounts
- AWS does not offer centralized tokenization or re-identification
- AWS does not make regulated data safe for AI and GenAI by default
Where AWS Security Stops
AWS security is designed to protect infrastructure, identities, and service access. It does not protect sensitive data at the data-element level or maintain privacy controls as data moves across services, accounts, regions, or AI pipelines.
When regulated data is used in AWS analytics, machine learning, or GenAI services such as SageMaker or Amazon Bedrock, there are no native controls to prevent exposure as data is reused.
Protegrity closes this gap by protecting sensitive data itself—so it remains secure across AWS services and AI workflows.
When Protegrity Become a Requirement
Enterprises typically add Protegrity to AWS environments when they:
- Use regulated data across multiple AWS services or accounts
- Train ML or GenAI models on sensitive data
- Share data across regions, teams, or business units
- Need provable AI data privacy and compliance controls
How Protegrity And AWS Work Together
AWS Responsibilities
- Cloud infrastructure and compute
- Analytics and AI services
- Identity and access management
- Scalability and availability
Protegrity Responsibilities
- Field-level tokenization and encryption
- Persistent protection across shared and replicated data
- AI data security and privacy enforcement
- Compliance controls that persist beyond individual services
Where Protegrity Fits in AWS
Protegrity operates as the enterprise data protection control layer for AWS, applying tokenization and encryption for privacy, compliance, and AI data security before data is used by analytics, machine learning, or GenAI services.
AWS executes services at scale. Protegrity controls data exposure across the cloud.
Proven ROI & Business Impact
This is not about adding another tool. It’s about enabling AWS to safely operate on regulated data. AWS enables analytics and AI in the cloud. Protegrity enables the safe use of regulated data for AI across AWS services.
If your AWS environment includes regulated data, Protegrity is the data protection layer AWS was never designed to provide.
Snowflake and protegrity – Capability Comparison
| Category | Capability | AWS | Protegrity |
|---|---|---|---|
| Security Model | Infrastructure & service security (shared responsibility) | Included | Not included |
| Data-element level protection | Not included | Included | |
| Identity & Access | IAM roles, policies, service access | Included | Not included |
| Data protection independent of IAM | Not included | Included | |
| Data Protection | Field-level tokenization | Not included | Included |
| Persistent encryption across services | Not included | Included | |
| AI & ML | AI / ML service execution (SageMaker, Bedrock) | Included | Not included |
| AI data privacy for training and inference | Not included | Included | |
| Multi-account / Multi-Region | Account & region isolation | Included | Not included |
| Consistent protection across accounts & regions | Not included | Included | |
| Data Movement | Secure service-to-service transfer | Included | Not included |
| Protection that persists as data moves | Not included | Included | |
| Compliance | Service-level controls & logging | Included | Not included |
| Centralized data protection policy | Not included | Included | |
| Compliance | Infrastructure compliance | Included | Not included |
| Persistent compliance for regulated data | Not included | Included |