Explore how an AI-powered investigation platform helps teams move from identifying a person of interest to discovering suspicious media, reviewing findings, and maintaining a structured investigation record
Where it looks
Interface simulation: an illustration of the workflow, not a live analysis
DeepFakeFinder
Follow the evidence across the open web
Project overview
DeepFakeFinder reduces the manual effort of finding possible deepfake videos of a target person. Instead of searching multiple websites by hand, the platform searches supported sources, collects relevant media, helps establish whether the target person appears, and assesses what remains for signs of manipulation.
Web intelligence, computer vision, and AI verification come together in one investigation workflow. Findings are presented in an organized dashboard and stored as cases for future review.
Teams can investigate a person of interest, identify potentially relevant videos across supported online sources, review suspicious findings, and preserve previous results within an organized case.
AI assists investigators, but final decisions should always include human review.
Multi-platform
Searches supported public sources in one investigation
AI-assisted
Relevance verification before detailed deepfake analysis
Case-based
Historical results retained with every investigation
Continuous
Scanning can repeat for newly published content
How it works
Investigator enters the target name
A case is created for the investigation
Public websites, supported social platforms and online media sources searched
Relevant videos and thumbnails collected
AI helps establish whether the target person appears
Relevant media is assessed for signs of manipulation
Previously reviewed content can be recognized and set aside
Findings are organized as investigation results
Interface simulation: an illustration of the workflow, not a live analysis
Investigator enters the target name
A case is created for the investigation
Public websites, supported social platforms and online media sources searched
Relevant videos and thumbnails collected
AI helps establish whether the target person appears
Relevant media is assessed for signs of manipulation
Previously reviewed content can be recognized and set aside
Findings are organized as investigation results
Project exclusiveness
Unified investigation
Interface simulation: an illustration of the workflow, not a live analysis
Market comparison
Search across supported online sources
Identity-focused verification
Deepfake video analysis
Investigation case management
Ongoing monitoring
Duplicate management
Centralized investigation dashboard
The architecture
Relevance is established before content is examined for signs of manipulation, and the case stays open
Investigation case
A case is created for the identity being monitored, and everything below stays attached to it
Possible sources may include
Stage 01: relevance verification
Media unrelated to the target is separated out before deeper investigation, keeping the case focused on media that matters.
Stage 02: authenticity assessment
Potential use cases
Identify deepfake-driven impersonation and influence threats. Help cyber intelligence teams identify suspicious videos impersonating executives, public officials, employees, or other individuals of interest: earlier discovery can support investigations into misinformation, impersonation fraud, social engineering, and influence campaigns.
Bring suspicious media into a structured investigation. Support investigators examining whether online video content may have been manipulated or artificially generated, while keeping relevant findings organized within a dedicated case.
Verify suspicious videos before they influence the story. Help journalists, researchers, and fact-checkers investigate viral or questionable videos before publication or redistribution, supporting more informed media verification.
Find misuse of executives and brand identities. Monitor for suspicious videos using the appearance or identity of executives, spokespersons, public representatives, or other individuals associated with an organization, so teams can respond to impersonation scams, fraudulent promotions, misleading advertisements, and reputational threats.
Support investigations involving synthetic media. Help authorized investigation teams locate potentially manipulated online media, organize publicly available findings, and review suspicious content during fraud, cybercrime, and digital evidence investigations.
Bring online media discovery into one investigation view. Support open-source intelligence teams by organizing relevant publicly available media and investigation findings for further analysis.
Watch for unauthorized synthetic representations. Help public figures, journalists, executives, creators, influencers, celebrities, and organizations identify suspicious videos that may misuse their identity or likeness.
Deployment strategy
01 · Define the investigation scope
Interface simulation: an illustration of the workflow, not a live analysis
Why this project matters
Deepfake threats often spread faster than teams can manually locate and review them.
Frequently asked questions
DeepFakeFinder is an AI-assisted deepfake investigation platform that helps teams discover suspected synthetic or manipulated videos across supported online sources, verify their relevance, assess potential deepfake indicators, and organize findings into investigation cases.
It reduces the manual effort required to search for and investigate suspected deepfake videos, bringing online discovery, identity-focused verification, deepfake analysis, case management, and ongoing monitoring into a single workflow.
No. DeepFakeFinder is designed for deepfake detection, synthetic media investigation, media verification, and threat monitoring. It does not create deepfake content.
Yes. AI can help identify and prioritize suspicious media, but context and investigation judgment remain important. Findings should be reviewed by qualified people before significant decisions or actions are taken.
Yes. Investigations that require ongoing monitoring can be revisited to help identify newly available content involving the same target.
Yes. Findings can be maintained within investigation cases, so teams can revisit historical results and understand how an investigation has developed over time.
DeepFakeFinder can support cybersecurity teams, digital forensics specialists, journalists, fact-checkers, researchers, OSINT analysts, brand protection teams, law enforcement support functions, and organizations concerned about deepfake impersonation.
Yes. Organizations can use it to investigate suspicious online videos involving executives, spokespersons, public representatives, or other individuals whose identity may be misused in synthetic media.
No. Deepfake detection is one part of the workflow. The platform is designed to help teams discover relevant media, investigate suspicious content, organize findings, preserve case history, and support ongoing monitoring.
The rest of the line
Where it runs
Each sector page covers the threat model, the controls, and the regulators that apply.
See how DeepFakeFinder searches supported sources, verifies possible matches, analyses media, and organizes findings into cases.
