AI-powered social media screening for safer, more inclusive, and compliant workplaces.
Fama is the world's largest social media screening and workplace misconduct prevention platform. As of 2026, its technical architecture leverages advanced Natural Language Processing (NLP) and Computer Vision to analyze public web data, identifying behavioral risks such as harassment, intolerance, and illegal acts. Positioned as a mission-critical tool for Enterprise HR and Compliance departments, Fama bridges the gap between traditional background checks and real-world online behavior. The platform is engineered to eliminate human bias from the screening process by automatically redacting protected class information (age, race, religion, gender) while focusing solely on behavior-based risk. Its 2026 market position is solidified through strategic integrations with every major Applicant Tracking System (ATS), providing a seamless, automated workflow for high-volume hiring. Fama complies with FCRA, GDPR, and EEOC regulations, making it a gold standard for global enterprises seeking to protect brand reputation and foster healthy company cultures through data-driven behavioral intelligence.
Fama is the world's largest social media screening and workplace misconduct prevention platform.
Explore all tools that specialize in misconduct detection. This domain focus ensures Fama Technologies delivers optimized results for this specific requirement.
Uses AI to identify and strip out metadata related to protected classes (gender, race, disability) before the report reaches the recruiter.
Proprietary NLP models capable of detecting context-specific slang and misconduct across 50+ languages.
Configurable risk categories (e.g., Harassment, Hate Speech, Illegal Acts) that can be toggled per job role.
Scans thousands of news sources and blogs in real-time to identify negative mentions of individuals.
Embedded legal workflow that manages the disclosure and authorization process digitally.
Bi-directional sync that feeds risk scores directly into the candidate profile in the ATS.
Attempts to cross-reference public data archives to find deleted content that remains in the public domain caches.
Initial consultation to define custom risk taxonomy and behavioral flags.
Integration with existing ATS (e.g., Greenhouse, Workday) via API keys.
Configuration of User Roles and Permissions within the Fama Dashboard.
Setting up Candidate Disclosure and Authorization workflows to ensure FCRA compliance.
Defining the 'Lookback Period' for social media data (e.g., 7 years).
Mapping Fama screening results to internal HR hiring stages.
Testing the automated trigger: 'Move to Screen' in ATS launches Fama report.
Training the recruitment team on interpreting Fama Risk Scorecards.
Establishing the 'Adverse Action' workflow for non-compliant candidates.
Go-live and periodic review of AI-flagging accuracy and bias metrics.
All Set
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Verified feedback from other users.
"Highly praised for its ease of integration and ability to uncover risks that traditional background checks miss. Users value the compliance peace-of-mind."
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