Data mining for sensitive information?

We have the solution you’ve been looking for.

See how fast your incident response team can data mine for sensitive personally identifiable information (PII) and build a list of affected individuals.

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Data Breach

Canopy’s Software-as-a-Service is the first known platform of its kind dedicated to the discovery of sensitive information, data breach review, and building lists of affected individuals for data breach notification.

Data Mining Personal Identifiable Information PII

Why Canopy for Incident
Response?

When an incident occurs, time is of the essence—combing through millions of documents to find affected PII requires a new approach. Emergent’s technology was designed by Canopy to reduce time, cost, risk, and effort associated with the defensible discovery of personally identifiable data.
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Accelerate Detection of Personally Identifiable Information

Canopy processes electronically stored information using proprietary algorithms pre-trained for sensitive information detection and extraction that goes well beyond the capabilities of regular expressions.

Assess Privacy Impact Within 72 Hours

Canopy's reports are designed to help you assess the impact of the breach before reviewing the data. Use the analytics to cull and organize documents in preparation for data mining affected individuals.

Generate a List of Unique Individuals

Canopy's coding technology and workflow are designed to resolve the relationships between individuals and their elements found across multiple documents. Canopy's machine learning model helps quickly extract, relate, and export a list of unique individuals.

Cloud-Native, Scalable, & Secure

Deployed on AWS

Autoscale

Encrypted at Rest

Encrypted in Transit

Containerized

Any Jurisdiction

Respond faster than your competitors

Get started with Canopy today. We'll set you up and train you quickly.
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Robust Upload

Upload or import from S3, Google Drive, Dropox, Office 365, or SFTP

Defensible Processing

Process uploaded information using standard e-discovery methods

Active Lookahead

Actively associate individuals with documents as the system learns

Detect & Classify

Automatic PII/PHI detection using Machine Learning

Anomaly Detection

AI-based detection of data anomalies, such as typos in Social Security Number

Entity Relating

Link and relate entities to build lists of affected individuals/data subjects

MapAccel

Map spreadsheet columns to entities and import entities while reviewing documents

Entity Resolution

De-duplicate and normalize related entities, even with nicknames or maiden names