← Blog  ·  April 28, 2026  ·  7 min read

OpenAI Privacy Filter vs AWS Comprehend PII — side-by-side comparison (2026)

Two managed PII detection APIs now compete for developer mindshare: OpenAI Privacy Filter (launched April 2026) and AWS Comprehend with its PII detection feature (available since 2020). They solve the same problem — find and redact personal data in text — but they come from very different architectural philosophies. This comparison covers accuracy, entity coverage, pricing, latency, and which use cases tilt the decision one way or the other.

Quick verdict

• OpenAI Privacy Filter: better for contextual PII in unstructured prose, simpler API surface, no AWS account required.
• AWS Comprehend PII: better for teams already on AWS who need audit trails, fine-grained IAM control, and tight CloudTrail integration.

Feature comparison

Accuracy: where each tool excels

OpenAI Privacy Filter uses an LLM backbone, which means it understands context. Given the sentence "Send the report to Sarah at the London office", it correctly flags PERSON: Sarah even without an email address or phone number next to it. AWS Comprehend uses a hybrid of ML classifiers and regex, which makes it extremely reliable for structured PII (SSNs in the format XXX-XX-XXXX, credit card numbers, formatted phone numbers) but more brittle on casual references to people and places.

For an independent benchmark, see our OpenAI Privacy Filter accuracy benchmark which tests precision and recall across entity types against a labeled dataset.

Pricing breakdown for common workloads

Processing 500 support tickets/month (~2,000 chars each)

• OpenAI Privacy Filter (via PrivacyFilter.run): Unlimited Monthly at $19/month. Cost: $0.038/ticket.
• AWS Comprehend PII: 500 × 20 units × $0.0001 = $1.00/month. Cheaper by volume — but you pay for AWS infrastructure (Lambda, API Gateway) on top.

Processing 50 documents/month (one-off)

• OpenAI Privacy Filter: $9 one-time Redact Pack.
• AWS Comprehend PII: ~$0.10 in API costs, but requires IAM setup time, credentials management, and SDK dependency.

The calculus changes for high-volume enterprise workloads. At 100,000 documents/month, AWS Comprehend's per-unit pricing can come out 60–70% cheaper — if you're already paying for AWS infrastructure anyway.

Developer experience

Calling OpenAI Privacy Filter via PrivacyFilter.run requires no account for the free tier:

import httpx

resp = httpx.post("https://privacyfilter.run/api/redact",
                  json={"text": "Contact John Doe at john@example.com"})
print(resp.json()["redacted_text"])
# → "Contact [PERSON_1] at [EMAIL_2]"

AWS Comprehend requires boto3, an IAM role, and a region endpoint:

import boto3

client = boto3.client("comprehend", region_name="us-east-1")
response = client.detect_pii_entities(
    Text="Contact John Doe at john@example.com",
    LanguageCode="en"
)
for entity in response["Entities"]:
    print(entity["Type"], entity["BeginOffset"], entity["EndOffset"])

AWS Comprehend returns character offsets only — you reconstruct the redacted string yourself. PrivacyFilter returns the redacted text and the entity list pre-processed, which saves 10–20 lines of glue code per integration.

When to choose OpenAI Privacy Filter

• You're processing conversational text or support tickets where PII is implied by context, not just formatted data.
• Your team is not on AWS and you want to avoid the IAM overhead.
• You need a fast prototype or one-off tool with zero infrastructure setup.
• You process fewer than 6,000 documents/month (the $19/month plan covers this completely).
• Your privacy policy requires that input text is never logged server-side. PrivacyFilter.run stores no input text; only rate limit metadata is retained.

When to choose AWS Comprehend PII

• You need more than 10 entity types — especially bank account numbers, driver's licenses, or passport numbers.
• You process multi-language documents and need reliable Spanish, French, German, or Japanese support.
• You need custom entity recognizers trained on your domain vocabulary.
• Your compliance team requires CloudTrail audit logs for every API call.
• You're already running a large AWS data pipeline and want to keep everything in the same account for billing and IAM simplicity.

Verdict

For a developer building a new product or adding PII scrubbing to an LLM pipeline, OpenAI Privacy Filter via PrivacyFilter.run is the faster, simpler default. For a team in an AWS-native data platform with compliance requirements that mandate audit logs and multi-language support, AWS Comprehend PII is the more mature choice.

See also: how Privacy Filter compares to Microsoft Presidio and our full PII tool alternatives guide.