Use Case

Document redaction automation

AI-Driven Redaction with LLM-Powered Document Discovery

The data redaction and data sharing workflow allows your staff to quickly find the correct documents thanks to LLM models and redact the data that is deemed as sensitive.

Our AI algorithms detect the sensitive data and thanks to the ML algorithms the precision and accuracy improves over time. With our human-in-the-loop approach, your staff is still in charge of the final review and can accept, amend and edit the redaction as needed.

Custom workflows allow for collaboration and sign offs from various stakeholder, before being shared.

This allows you to share documentation and information safely and securely with the interested parties.

Document redaction automation

01
Data Source

Secure collection and ingestion of structured and unstructured data from multiple enterprise systems and formats.

02
AgentricAI Platform

Our intelligent processing hub analyzes and routes incoming data through the entire redaction workflow.

03
Information and document deduplication

Advanced algorithms identify and eliminate redundant documents to optimize processing efficiency and ensure consistency.

04
Sensitive information detection

AI-powered recognition automatically identifies PII, PHI, financial data, and other confidential information requiring protection.

05
Data masking and anonymization

Sophisticated techniques precisely redact sensitive elements while preserving data utility and contextual integrity.

04
Internal regulatory sign off

Automated compliance verification ensures all redaction meets organizational policies and regulatory requirements.

05
Automatic packaging and sharing

Securely formatted redacted data is prepared and distributed to authorized recipients with comprehensive audit trails.

Let’s talk insurance

Have a question, idea, or specific request? We're all ears and eager to help. Reach out to us, and we'll be delighted to assist you.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.