NOI vs Protecto: LLM PII Protection Compared [2026]
See how NOI stacks up against its alternative, Protecto
NOI vs Protecto: LLM Privacy Proxy vs AI Data Privacy Platform
Page Introduction
Protecto is a broad AI data privacy platform covering prompts, RAG, training data, and agentic AI. NOI is a purpose-built LLM privacy proxy that deploys with a one-line code change. Both protect PII. They take fundamentally different approaches to get there.
Product Overviews
NOI
NOI is a PII-tokenizing reverse proxy for LLM API traffic built by Enigma Vault. It sits between your application and model providers (OpenAI, Anthropic, Gemini, Grok, and others), detecting sensitive data, replacing it with deterministic tokens, forwarding a clean prompt to the model, and restoring real values in the response. Integration requires changing the base_url parameter in your existing OpenAI SDK client. One line of code. Built on PCI Level 1 certified infrastructure. Free tier available (1M tokens/month, no credit card).
Protecto
Protecto positions itself as a "privacy control plane for AI." It covers PII detection across prompts, responses, RAG pipelines, training data, and agentic AI workflows. Protecto uses a proprietary "DeepSight" detection engine, claiming 99% recall across 200+ sensitive data types in 50+ languages. It offers context-preserving tokenization (which Protecto calls "masking"), RBAC-based data access controls, and pre-built compliance policies for HIPAA, GDPR, PDPL, and DPDP. Founded in 2021, headquartered in the US with operations in India. Available on Google Cloud Marketplace.
Feature-by-Feature Comparison
| Feature | NOI | Protecto |
|---|---|---|
| Primary Focus | LLM API traffic protection (prompt/response tokenization) | Broad AI data privacy platform (prompts, RAG, training, agents, warehouses) |
| Integration Method | Transparent reverse proxy. Change base_url. One line of code. | SDK integration or API calls. Requires instrumenting application code or pipelines. |
| Deployment Speed | Minutes. No infrastructure changes. | Days to weeks depending on scope and pipeline complexity. |
| Detection Engine | Microsoft Presidio with custom NER models. | Proprietary "DeepSight" engine. Claims 99% recall, 200+ entity types, 50+ languages. |
| Tokenization Approach | Deterministic. Same value always maps to same token. Preserves entity relationships. | Context-preserving "masking." Claims 85% semantic similarity retention. |
| Round-Trip Detokenization | Yes. Automatic on every response. | Yes. Available for authorized users via RBAC. |
| Scope of Protection | LLM API traffic (prompts and responses in transit). | Broader: prompts, RAG, training data, agent chains, data warehouses. |
| Fail-Safe Behavior | Default-block. If tokenization fails, request is blocked. Not configurable. | Configurable guardrails with block/mask options. Default behavior not prominently documented. |
| Context Phrase Neutralization | Yes. Replaces trigger terms to prevent LLM safety refusals. | Not documented as a feature. |
| Compliance Certifications | PCI Level 1 (Enigma Vault), ISO 27001, HIPAA/GDPR/SOX ready. | Claims HIPAA, GDPR, PDPL, DPDP compliance policies. |
| SSE Streaming Support | Yes. Native SSE for OpenAI and Anthropic. | Supports sync and async. Streaming not prominently documented. |
| Pricing | Free: 1M tokens/month. Pro: $50/mo. Enterprise: custom. | Not publicly listed. Contact sales. |
The Verdict
If your primary need is protecting LLM API traffic with minimal integration effort, NOI gets you from zero to protected in minutes with a one-line code change. If you need enterprise-wide AI data governance spanning RAG pipelines, training data, agent workflows, and data warehouses, Protecto covers a broader surface area.
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Frequently Asked Questions
Partially. Protecto covers a much broader scope including RAG pipelines, training data, data warehouses, and agent chains. NOI is focused specifically on LLM API traffic protection via a reverse proxy. For teams that only need prompt and response tokenization with minimal integration effort, NOI is the faster and more targeted solution. For enterprise-wide AI data governance, Protecto covers more ground.
No. Protecto requires SDK integration or API instrumentation, which means modifying your application code or data pipelines. NOI deploys by changing a single base_url parameter in your existing OpenAI SDK client. No new SDK, no pipeline changes, and no infrastructure modifications are required.
Protecto claims 99% recall with its proprietary DeepSight engine across 200+ entity types and 50+ languages. NOI uses Microsoft Presidio with custom NER models. Both approaches are capable, but independent side-by-side benchmarks are not publicly available. Evaluate based on your specific data types and languages.
No. NOI is focused on real-time LLM API traffic, meaning prompts sent to and responses received from model providers. It does not cover RAG document indexing, training data sanitization, or data warehouse scanning. If you need protection across those additional surfaces, Protecto or a combination of tools may be more appropriate.
NOI blocks the request by default when tokenization fails. This fail-safe behavior is not configurable, ensuring PII never leaks to a model provider even during system errors. Protecto offers configurable guardrails with block or mask options, but its default fail-safe behavior is not as prominently documented.
NOI is more practical for startups. The free tier (1M protected tokens per month, no credit card) and one-line integration mean you can add PII protection in minutes without a procurement process. Protecto is better suited for enterprises that need a comprehensive AI data governance platform.