SOC 2 Compliance

from blindfold import Blindfold
from openai import OpenAI

blindfold = Blindfold(api_key="your-key")
openai_client = OpenAI(api_key="your-openai-key")

customer_message = (
    "Hi, I'm Alex Chen. My email is alex.chen@example.com "
    "and my phone number is (555) 123-4567. "
    "I need to update my billing address to 742 Evergreen Terrace."
)

# Tokenize PII — creates an audit log entry
tokenized = blindfold.tokenize(customer_message)
# → "Hi, I'm <Person_1>. My email is <Email Address_1>
#    and my phone number is <Phone Number_1>.
#    I need to update my billing address to <Address_1>."

# Audit log records: timestamp, 4 entities detected, method: tokenize
print(f"Entities detected: {tokenized.entities_count}")
for entity in tokenized.detected_entities:
    print(f"  [{entity.type}] → {entity.token}")

# Send only tokens to AI provider
completion = openai_client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": tokenized.text}],
)

# Restore real values in the response
restored = blindfold.detokenize(
    completion.choices[0].message.content,
    tokenized.mapping,
)
print(restored.text)

import { Blindfold } from '@blindfold/sdk';
import OpenAI from 'openai';

const blindfold = new Blindfold({ apiKey: 'your-key' });
const openai = new OpenAI({ apiKey: 'your-openai-key' });

const customerMessage =
  "Hi, I'm Alex Chen. My email is alex.chen@example.com " +
  'and my phone number is (555) 123-4567. ' +
  'I need to update my billing address to 742 Evergreen Terrace.';

// Tokenize PII — creates an audit log entry
const tokenized = await blindfold.tokenize(customerMessage);
// → "Hi, I'm <Person_1>. My email is <Email Address_1>
//    and my phone number is <Phone Number_1>.
//    I need to update my billing address to <Address_1>."

console.log(`Entities detected: ${tokenized.entitiesCount}`);
for (const entity of tokenized.detectedEntities) {
  console.log(`  [${entity.type}] → ${entity.token}`);
}

// Send only tokens to AI provider
const completion = await openai.chat.completions.create({
  model: 'gpt-4o-mini',
  messages: [{ role: 'user', content: tokenized.text }],
});

// Restore real values in the response
const restored = await blindfold.detokenize(
  completion.choices[0].message.content,
  tokenized.mapping,
);
console.log(restored.text);

from blindfold import Blindfold

client = Blindfold(api_key="your-key")

customer_record = (
    "Customer: Alex Chen, email: alex.chen@example.com, "
    "SSN: 123-45-6789, account balance: $15,230.00"
)

# Encrypt PII before storage
encrypted = client.encrypt(customer_record, encryption_key="your-encryption-key")
# Store encrypted.text in your database — auditor sees encrypted values

print(encrypted.text)
# → "Customer: aGVsbG8..., email: dGVzdA...,
#    SSN: c2VjcmV0..., account balance: $15,230.00"

# Decrypt when authorized access is needed
decrypted = client.decrypt(encrypted.text, encryption_key="your-encryption-key")
print(decrypted.text)  # Original text restored

import { Blindfold } from '@blindfold/sdk';

const client = new Blindfold({ apiKey: 'your-key' });

const customerRecord =
  'Customer: Alex Chen, email: alex.chen@example.com, ' +
  'SSN: 123-45-6789, account balance: $15,230.00';

// Encrypt PII before storage
const encrypted = await client.encrypt(customerRecord, {
  encryptionKey: 'your-encryption-key',
});
// Store encrypted.text in your database

console.log(encrypted.text);

// Decrypt when authorized access is needed
const decrypted = await client.decrypt(encrypted.text, {
  encryptionKey: 'your-encryption-key',
});
console.log(decrypted.text); // Original text restored