Privacy Engine

Develop AI Workflows with privacy-preserving healthcare data

De-identify clinical notes, medical imaging, and audio at scale. HIPAA-compliant infrastructure that AI teams integrate in minutes, not months.

deidentify.py
from integral import Integral

client = Integral(api_key="int_live_...")

# De-identify a clinical note
result = client.deidentify(
    content="Patient John Smith, DOB 03/15/1985, "
            "presented at Springfield General "
            "with acute chest pain...",
    modality="clinical_note",
)

print(result.text)
# "Patient [REDACTED], DOB [REDACTED],
#  presented at [REDACTED] with acute
#  chest pain..."

print(result.phi_count)   # 3
print(result.compliant)   # True

Trusted by healthcare and AI teams

0%

Data utility preserved

on average across all datasets

0 days

Expert Determination

vs. 3–6 months traditionally

0B+

PHI entities processed

across regulated datasets to date

Multi-modal

Privacy infrastructure for every data type

Purpose-built de-identification for the unstructured healthcare data that AI models need most.

Clinical Notes

De-identify free-text medical records, discharge summaries, and pathology reports with healthcare-native NER.

DICOM Studies

Strip PHI from DICOM headers and burned-in pixel annotations across all major imaging modalities automatically.

CT Scans

Process volumetric CT datasets at scale. Remove patient identifiers from metadata and embedded overlays.

MRIs

De-identify MRI sequences including structural, functional, and diffusion imaging with full DICOM compliance.

Ultrasound

Redact burned-in PHI from real-time and stored ultrasound imagery including cine loops and 3D volumes.

X-Ray & Radiographs

Automated PHI removal from digital radiography, mammography, and fluoroscopy studies at any resolution.

Pathology Slides

De-identify whole slide images and digital pathology datasets. Strip patient data from slide labels and metadata.

Genomic Data

Process genomic indicators, variant call files, and sequencing metadata with re-identification risk scoring.

Voice & Audio

Redact patient identifiers from recorded consultations, telehealth sessions, and dictated clinical notes.

De-identification that's certified, flexible, and deployable anywhere

Most tools anonymize data. Integral certifies it under HIPAA Expert Determination — with flexible remediation strategies and deployment options that fit your infrastructure.

Certified, not just de-identified

Every dataset receives a signed Expert Determination certification — a PDF opinion backed by qualified statistical experts that justifies low re-identification risk based on your data, use case, and privacy posture. Not a black-box score. A defensible artifact for regulators, partners, and legal teams.

Flexible remediation strategies

Preserve geographic precision over demographics. Retain clinical dates at the cost of other entities. Replace PHI with synthetic entities that hide in plain sight. Integral's remediation adapts to what your data consumers need — not a one-size-fits-all checklist.

Cloud or self-hosted — your choice

Deploy as a fully managed cloud platform with dashboards, team management, and usage analytics. Or run the same core engine inside your VPC, on-prem, or air-gapped environment. Same API, same capabilities — your data, your infrastructure.

Start de-identifying healthcare data

Book a demo to see how Integral handles your data types — clinical notes, medical imaging, audio, and more.