AI PRIVACY GATEWAY · REVERSIBLE TOKENIZATION

Protect Sensitive Data Before AI Sees It

Protect sensitive data before AI sees it. PrivoNest combines local data understanding, multilingual protection and easy integration for your organization’s AI and data workflows.

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Production Languages
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Country Profiles
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Transformations
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Security Detector Categories

37 production languages · selected examples shown below

TRY THE LIVE ENGINE

Your text. Protected in seconds.

Try up to 50 characters. No account or API key needed.

0 / 50 characters

This live test sends text to this PrivoNest deployment. Avoid entering real secrets or personal information.

Privacy, Not Just Regex

Easy-to-integrate protection for multilingual data, AI prompt privacy and supported application workflows.

🌍

37-Language Detection

Production language packs span Latin, Arabic, Indic, CJK, Cyrillic, Greek, Thai and other supported scripts.

🪪

Country-Aware Identity Detection

153 country profiles include 52 strong-format and 101 baseline-contextual profiles for local identity, tax, health, banking and registration workflows.

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Hybrid NLP + Deterministic Rules

spaCy NER, contextual patterns, normalization and checksum validators work together instead of relying on one technique.

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7 Protection Strategies

Label, redact, partial mask, hash, tokenize, detokenize and remove sensitive values for different workflows.

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Documents, OCR & Structured Data

Protect supported text, JSON, PDF, DOCX, XLSX, CSV, images, email, DICOM and transcript workflows.

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AI Privacy Guard

A Python guardrail SDK can protect prompts before OpenAI, Claude, Gemini, Ollama, LangChain or LlamaIndex calls.

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Reversible Tokenization

Create PrivoNest PV1 tokens for trusted workflows and reveal them through an authenticated API when authorized.

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Automatic Inference

Language and country inference can activate relevant packs without forcing every application to hard-code routing logic.

How It Works

Three steps from raw content to policy-safe output.

1

Send text, JSON or a supported file

POST content to /v1/hide with your API key. Language and country hints can be explicit or inferred.

2

PrivoNest detects & validates

Multilingual NER, deterministic recognizers, context rules, normalizers and validators identify sensitive entities.

3

Apply the protection strategy

Return labels, redaction, partial masks, hashes, reversible tokens or removed values depending on the selected strategy.

Privacy layer in action

Protect Data Across the Workflow

The same PrivoNest engine can detect sensitive values, transform them for a downstream system, preserve useful structure, and restore reversible tokens only when your application chooses to.

01 · DETECT

Detect at Ingestion

  • • PII / identity recognition
  • • Language & country inference
  • • Metadata and detection spans
02 · PROTECT

Protect Before AI

  • • Scoped AI aliases
  • • Redact / partial / hash
  • • Reversible tokenization
03 · PROCESS

Keep Workflows Useful

  • • JSON path policies
  • • Document-preserving output
  • • Format-aware transformations
04 · RESTORE

Restore When Authorized

  • • PV1 reversible tokens
  • • Application-side aliases
  • • Explicit reveal endpoint
STABLE · PYTHON SDK v1.0.5

PrivoNest AI Privacy Guard

Add a privacy layer between your application and an LLM. Sensitive values are detected before the model call, replaced with scoped placeholders, and matching placeholders can be restored in the application response.

✓ OpenAI / Claude / Gemini
✓ Ollama / LangChain / LlamaIndex
✓ Short-lived alias mapping
✓ Uses your existing PrivoNest API
View SDK Guide Download SDK
guardrail.py 
from openai import OpenAI
from privonest_guardrail import Guard

# Two-line privacy integration
guard = Guard()
client = guard.wrap(OpenAI())

# App prompt
"My name is Ali and my email is ali@example.com"

# What the model can receive
"My name is [PN_NAME_1] and my email is [PN_EMAIL_1]"
Bring your own AI

Works With the AI Stack You Already Use

See Guard SDK adapters →
OpenAI
Claude
Gemini
Ollama
LangChain
LlamaIndex

PrivoNest is the privacy layer; your client keeps control of the model provider and its own provider API key. The PrivoNest SDK is v1.0.5 stable; third-party provider adapters should still be integration-tested against the exact provider/library versions used in production.

Built for Sensitive-Data Industries

Protect PII before it moves into analytics, support systems, documents, AI applications or downstream APIs.

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Healthcare

Patient identifiers, clinical text, health IDs, documents, images and DICOM-oriented privacy workflows.

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Financial Services & Fintech

Cards, IBANs, bank details, tax identifiers, national IDs and customer data before AI or processing.

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AI & SaaS

Prompt protection for copilots, RAG applications, support bots and internal AI tools.

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Customer Support & BPO

Redact sensitive information in email, chat, tickets, transcripts and exported support data.

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Education

Student IDs, contact information, enrollment records and sensitive documents.

⚖️

HR, Legal & Operations

Employee, applicant, contract and identity information in internal workflows and AI-assisted processing.

EASY INTEGRATION

Privacy where your work happens.

Connect selected content from email, documents or cloud workflows to your AI applications. Keep control of what you share.

● ● ●Email → AI assistantILLUSTRATIVE DEMO
Gmail
Selected email

Your authorized application supplies the text

Customer request

PrivoNest
Receive
OpenAIClaudeOllama
Connected AI application
PROTECTED CONTEXT

Waiting for selected content…

Read selected content through your authorized connector.Automatic walkthrough
OpenAISupported model clientClaudeAnthropic SDK adapterGeminiSupported SDK adapterOllamaLocal model workflowLangChainSupported adapterLlamaIndexSupported adapterEmailCustom API workflowGoogle DriveCustom API workflow

Email, Drive, cloud and RAG examples require your authorized source integration. They do not imply native account sync, monitoring of chatbot websites or provider partnerships.

Explore integration patterns →

API + AI PRIVACY GUARD

Add protection.
Keep your workflow.

Send selected text to the protection API or wrap a supported AI client with the Python SDK. Keep credentials on your server and check the protected result before forwarding it.

01 Receive authorized content

02 Detect and transform sensitive details

03 Forward protected context

Read the SDK guide → API documentation →
● ● ●protect_with_api.pyPYTHON
Writing the integration

Preparing selected content…

Automatic typing · illustrative outputServer-side integration

PRIVACY CONTROLS & REVIEW

Put a policy behind the protection.

Register connected applications, assign saved policies and inspect gateway outcomes. Keep vendor assessments, risk notes and readiness evidence together for human review.

01

Applications & policies

Explicitly register an app and assign scoped access.

02

Gateway activity

Inspect outcomes for configured traffic routed through PrivoNest.

03

Review & evidence

Record responsibility, assessments and follow-up work.

● ● ●Privacy workspaceSIMULATED

These controls support AI privacy and governance work. They are not automatic application discovery, complete AI governance, or a compliance certification.

See how application policies work →

See It In Action

Same endpoint, multiple scripts and country-aware protection — selected language examples below.

🇬🇧 English · en
# Request
POST /v1/hide
{
  "text": "Contact me at sara@mail.com",
  "language": "en",
  "strategy": "label"
}
# Response
{
  "result": "Contact me at [EMAIL]",
  "status": "success"
}
Reference scenarios

Three Ways Startups Can Use PrivoNest

These are implementation patterns based on current engine capabilities

More Use Cases →
AI STARTUP
🤖

Protect User Prompts Before Any LLM

Wrap the model client so names, emails and local identifiers can be replaced before an external LLM receives the prompt.

View scenario →
MULTILINGUAL FINTECH
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Handle Local IDs and Mixed-Language Text

Use country-aware rules, validators and code-switching support for workflows where English and local-language data appear together.

View scenario →
DOCUMENT WORKFLOW
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De-identify Files Without Building Separate Pipelines

Send PDFs, office files, images, email, DICOM or transcripts through one privacy engine and receive protected output plus detections.

View scenario →
FAQ

Common Questions

Is OpenAI required to use PrivoNest Guard?＋
No. OpenAI is only one model-provider adapter. The v1.0.5 SDK also includes Claude, Gemini, Ollama, LangChain and LlamaIndex adapters. Your application selects the provider.
What is the difference between masking and tokenization?＋
Masking/redaction changes or removes sensitive values for safe processing. PrivoNest reversible tokenization creates a protected PV1 token that can later be restored with the configured secret and an authorized reveal flow.
How much multilingual and country coverage is exposed?＋
The current engine reports 37 production languages and 153 country profiles. The current taxonomy contains 52 strong-format and 101 baseline-contextual country profiles; exact per-country entity coverage is machine-readable through /v1/capabilities.
Do I need a privacy specialist to integrate the basic API?＋
The product is designed for easy integration: a REST endpoint for data protection and a lightweight Python guard for LLM calls. Complex compliance programs still require appropriate legal and security review.
Does PrivoNest sell my data or train AI on my API payloads?＋
No. PrivoNest does not sell personal data and does not use customer API payloads to train AI models. PII-processing payloads are designed to be processed for the requested operation without intentional persistence. Account/contact data required to operate the service is described in the Privacy Policy.
Where can I see exact engine capabilities?＋
Use the API Docs for examples and GET /v1/capabilities for the machine-readable list of languages, country profiles, document types, transformations, validators and runtime dependency status.

Simple Pricing

Start free. Scale as you grow.

Free

Try it out

$0
  • —100 starter Privacy Credits
  • —All 37 production languages
  • —API key included
  • —Email support
Get Started
Most Popular

Pro

For production workloads

$9 / credit pack
  • —50,000 Privacy Credits per pack
  • —All 37 production languages
  • —Priority email support
  • —Manual account activation after payment
Buy Pro — $9

Enterprise

For large-scale usage

Custom
  • —Custom credit volume
  • —All 37 production languages
  • —Country-aware profiles & documents
  • —Integration support
  • —Dedicated onboarding support
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Protect Sensitive Data Before It Spreads

Use one PrivoNest account for PII/file protection and AI Privacy Guard.

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Need integration, AI guardrail or production support?
📧 support@privonest.cloud