Protegrity Alternative
Protegrity vs Protecto​
Tokenizing PII without retaining context kills AI accuracy
Protecto is the only data privacy tool that offers smart tokenization to retain context, scan PII with full accuracy, and facilitate role based access control in AI systems.
- Trusted by Engineering Teams Building AI at Scale
Why Protegrity falls short in critical areas?
While Protegrity’s capability in identifying and masking sensitive data is satisfactory, it is not built for modern enterprise grade AI systems.Â
- Lacks context: Built primarily for hybrid environments, Protegrity only retains the format, not the context. The result? AI hallucinations, compliance risks, poor quality analysis.
- Lower integration flexibility: Tightly bound to Azure, Protegrity lacks the APIs which gives the flexibility to integrate easily in a multi cloud setup.
- Missing contextual scanning: Scans PII by identifying each data rather than understanding the full context, resulting in false positives and negatives.
- Lower security: Uses a vaultless, algorithmic token generation using static codebooks that is less secure compared to Protecto’s entropy based tokenization
The ideal tool built for enterprise data, optimized to scale
- Simple APIs: Use sync and async APIs to integrate with any part: preprocessing, context data, prompt, or response.
- Contextual scanning: Understands the full context of prompt to intelligently and accurately identify PII across structured and unstructured text.
- Higher security: Uses intelligent, entropy based tokenization ensures strong anonymization to lower re-identification risk.Â
- Context based access control: Mask and unmask data based on role and context so only the authorised users access data they are supposed to see.Â
- Deterministic, consistent tokenization: Generates intelligent, entropy based tokens that consistently masks data throughout its life cycle, while giving AI context in the type of data.Â
COMPARISON
Protegrity vs. Protecto
Lets summarize the capabilities and features to help you make a decision.
| Features | Protegrity | Protecto |
|---|---|---|
| API-first tokenization | ! API tightly bound to Azure Functions | ✓ REST APIs, flexible and easy to integrate |
| Format-preserving tokenization | ! Retains format but lacks context for AI | ✓ Tokens retain context & format for AI/analytics |
| Deterministic tokenization | ✓ Deterministic supported, but context issues remain | ✓ Consistent tokens for same input |
| Custom tokenization policies | ! Vaultless tokenization with less flexibility | ✓ Highly flexible, define token type and patterns |
| Cloud-agnostic deployment | ✕ Primarily optimized for Azure, less depth elsewhere | ✓ Containerized, works across any cloud or on-prem |
| Unstructured data detection | ✕ Mainly structured data, weak on unstructured/context | ✓ Detects structured & unstructured data with context |
| Easy deployment & automation | ✕ Complex setup, high engineering effort | ✓ Lightweight, quick to deploy, automation-friendly |
| Strong governance & RBAC | ✕ Strong enterprise RBAC, but complex to manage | ✓ API-driven RBAC & policy enforcement |
| Detailed audit logging | ! Audit logging exists but requires extra setup | ✓ Logs every tokenization/detokenization call |
| Scalability & performance | ✕ Cloud-native, scales with distributed processing | ✓ Highly scalable for enterprise & legacy workloads |
Built for Enterprise. Optimized for Scale.
On-Premises or SaaS
Deploy Protecto on your servers or consume it as SaaS. Either way, get the full benefits including multitenancy.
Simple APIs
Use sync and async APIs to integrate with any part: preprocessing, context data, prompt, or response.
Auto-scale
Protecto's architecture scales to process billions of rows or runs lightweight on-edge devices, offering versatility and efficiency.
Trusted by Industry Leaders​
See why businesses around the world choose Protecto for their AI data security and privacy needs.
