Identify, Redact, and Replace Personally Identifiable Information in Unstructured Text

Your Data, Your Way

We apply the latest advancements in transformer architectures to pick up PII based entirely on context, which makes us particularly effective on semi-structured and unstructured data.

With Private AI data, security, and machine learning teams can:

  • Accurately redact data like ASR transcripts, chat logs, and electronic health records with less than half the error rate compared to alternatives.
  • Retain full ownership of your data; it’s never shared with us, and never leaves your infrastructure.
  • Identify and redact text in 52 languages (and growing).
  • Configure output extensively including turning entities on/off, add block or allow lists, and complying with privacy regulations like GDPR, LGPD, HIPAA, and more.
  • Custom entity types developed with the few shot learning techniques Private AI uses.
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Built by experts from:

How It Works

Private AI is deployed via a single container on-prem so you can easily add our powerful redaction capabilities to any data workflow. The container is accessed via a REST API and can be easily customizable depending on your team’s needs.

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PII IDENTIFICATION

Privacy is More Than a ML Model​

Private AI detects more than 50 different entity types of personally identifiable information (PII) across 52 languages. Using our contextually aware ML models, we go beyond traditional entity detection to recognize many different kinds of direct and quasi-identifiers.

What is and isn’t PII gets complicated, and Private AI’s team of privacy experts ensures our system works in compliance with major legislation like GDPR, CPRA, and HIPAA.

Private AI can be easily implemented as a filter to screen for PII in any data flow or database.

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{
  "result": "Hi [NAME_1], [NAME_2] this side. It's been a while since we last met in [LOCATION_CITY_1].",
  "result_fake": null,
  "pii": [
    {
      "marker": "NAME_1",
      "text": "John",
      "best_label": "NAME",
      "stt_idx": 3,
      "end_idx": 7,
      "labels": {
        "NAME": 0.8446
      }
    },
    {
      "marker": "NAME_2",
      "text": "Grace",
      "best_label": "NAME",
      "stt_idx": 9,
      "end_idx": 14,
      "labels": {
        "NAME": 0.8399
      }
    },
    {
      "marker": "LOCATION_CITY_1",
      "text": "Berlin",
      "best_label": "LOCATION_CITY",
      "stt_idx": 63,
      "end_idx": 69,
      "labels": {
        "LOCATION_CITY": 0.8778,
        "LOCATION": 0.8512
      }
    }
  ],
  "api_calls_used": 1,
  "output_checks_passed": true
}
TEXT DE-IDENTIFICATION

Redact at Higher Than Human Accuracy

Private AI can replace all the PII detected with unique identifiers (ie. NAME_1, CVV_3, CREDIT_CARD_2) to produce redacted transcripts or de-identified data. Alternatively, replace PII with a mask character. Look at our docs to learn more.

‍Unrivalled Accuracy

  • No third party access
  • No regexes
  • Real-time redaction
  • Complies with GDPR, HIPAA, CPRA, and more
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SYNTHETIC PII GENERATION

Never Use Transformers Without Privacy Mitigation​​

After PII is removed, Private AI can generate synthetic PII to replace all the PII  found with fake data that fits the surrounding context.

The synthetic PII generator never sees the original data, eliminating sensitive data leakage. The resulting text further reduces re-identification risk, as an adversary must first identify what PII is real. Good luck finding a piece of straw in a pile of hay!

Taking production data and replacing all PII with synthetic data also minimizes data shift from the original data, which is highly beneficial when creating ML models.

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TOKENIZATION & PSEUDONYMIZATION

Reverse PII Removal As Needed

Replace PII with encrypted tokens using Private AI’s tokenization feature. Sometimes referred to as pseudonymization, tokenization preserves the utility of the data while still protecting what’s sensitive.

Tokenization is reversible, allowing you to easily recover the original data. Contact us for documentation and access.

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Supported Entities
Supported Languages
  • Address
  • Age
  • Bank Account
  • Blood Type
  • City
  • Condition
  • Coordinates
  • Country
  • Credit Card
  • Credit Card Expiration
  • CVV
  • Date
  • Date Interval
  • Date of Birth
  • Dose
  • Drivers License
  • Drug
  • Email Address
  • Event
  • Family Name
  • Filename
  • Gender Sexuality
  • Given Name
  • Healthcare Number
  • Injury
  • IP Address
  • language
  • Marital Status
  • Medical Process
  • Money
  • Name
  • Numerical PII
  • Occupation
  • Organization
  • Origin
  • Passport Number
  • Password
  • Phone Number
  • Physical Attribute
  • Political Affiliation
  • Religion
  • Routing Number
  • SSN
  • State
  • Statistics
  • Time
  • URL
  • Username
  • Vehicle ID
  • ZIP
  • Zodiac Sign
For a detailed listing of entities complete with descriptions, examples, and regulatory compliance information visit our docs.
  • English
  • French
  • German
  • Hindi
  • Italian
  • Korean
  • Portuguese
  • Russian
  • Spanish
  • Tagalog
  • Ukranian
  • Arabic
  • Bengali
  • Belarusian
  • Bulgarian
  • Burmese
  • Catalan
  • Croatian
  • Czech
  • Danish
  • Dutch
  • Estonian
  • Finnish
  • Greek
  • Hebrew
  • Hungrian
  • Icelandic
  • Indonesian
  • Khmer
  • Latvian
  • Lithuanian
  • Luxembourgish
  • Malay
  • Moldovan
  • Norwegian (Bokmål)
  • Persian (Farsi)
  • Polish
  • Punjabi
  • Romanian
  • Slovak
  • Slovenian
  • Swahili
  • Swedish
  • Tamil
  • Thai
  • Turkish
  • Vietnamese
  • Mandarin (simplified)
  • Japanese
  • Cantonese (traditional)*
  • Haitian Creole*
  • Mandarin (Traditional)*
For a detailed listing of languages complete with support levels, ISO code, and release details visit our docs.
* Coming soon

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