Automated Document Redaction & FOIA
Automatically redact documents to save time and eliminate human error for FOIA compliance across document formats.
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Problem
Manual document redaction is slow, error-prone, and costly, making FOIA compliance and privacy protection difficult to scale across growing data volumes and millions of documents.
Time sensitive
Human reviewers must manually locate and redact sensitive information line by line
Human error
Missed redactions or over-redaction create legal and reputational risks
Scalability limits
Agencies struggle to handle large volumes of records and data formats efficiently
Inconsistent results
Redaction quality varies across teams and document types
Compliance pressure
FOIA, privacy, and security mandates demand rapid, accurate turnaround
Solution
Seekr’s agentic AI automates redaction with precision and speed—ensuring consistent, compliant results across millions of pages and document types.
Automation
Instantly identifies and redacts PII, classified data, and sensitive content
Accuracy
Reduces human error with AI-trained entity recognition and contextual understanding
Scalability
Processes large document sets across PDFs, Word files, and scans in minutes
Compliance
Maintains FOIA, Privacy Act, and agency-specific standards automatically
Efficiency
Cuts review time from hours to seconds while improving consistency and auditability
How it works
Agentic AI identifies sensitive entities and patterns (names, SSNs, locations, classifications) across structured and unstructured text within documents
AI agents apply configurable rules and policies to redact and replace content across multiple document formats at scale
SeekrFlow™ generates reports for reviewer validation, audits and compliance tracking
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more accurate model responses
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faster to prepare a dataset vs. others
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minutes or less to build a production-grade LLM
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See it in action
See how this AI solution works for your team. Request a live walkthrough with one of our experts and explore how it can adapt to your unique workflows and data.
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