Real-time call analysis
Evaluates incoming audio and video throughout a live interaction, rather than relying on a single convincing moment or only analyzing a recording afterward.
Diopter AI is a deepfake and AI social engineering detection platform for organizations handling high-trust calls involving payments, access, identity verification, and hiring. It analyzes audio, video, participant identity, conversation behavior, and policy alignment to surface risks while an interaction is still live.
Diopter AI is a real-time defense platform for deepfakes and AI-enabled social engineering. It analyzes audio and video streams during calls and evaluates the interaction as a structured conversation event rather than treating it as a single media artifact. The system is designed to identify synthetic voices, manipulated video, AI-generated identities, and behavioral patterns associated with fraud.
Its purpose is to help teams assess whether a caller is genuine and whether a request follows the organization’s required process before money, credentials, access, or an identity record changes hands. Diopter checks participants against a directory and meeting platform, watches for authority, urgency, isolation, and escalation, and flags requests that conflict with corporate, security, or finance policies.
The product is aimed at high-trust workflows such as financial approvals, help desk credential resets, remote interviews, vendor interactions, and executive communications. Alerts can include evidence and a recommended action for security teams while the call is in progress. Diopter also offers media analysis outside live calls through its detector tools and a Claude connector for checking linked images, video, and audio.
Evaluates incoming audio and video throughout a live interaction, rather than relying on a single convincing moment or only analyzing a recording afterward.
Looks for indicators of cloned speech, AI-generated audio, face swaps, and manipulated video, including vocal, facial, spectral, timing, lighting, and boundary signals.
Compares participants with the organization’s directory and meeting platform to flag an outsider presenting themselves as an internal person or trusted role.
Tracks authority claims, urgency, isolation, escalating pressure, secrecy, and requests that emerge at the end of an attack sequence.
Identifies requests that violate company security, finance, or other approval processes and warns users not to act without independent verification or the proper process.
Supports image, video, and audio checks through detector tools. In Claude, users can submit a direct, publicly reachable HTTPS media link and receive a verdict, confidence score, and full-report link.
Finance or deal teams can receive warnings when an apparent executive, vendor, or other participant combines identity anomalies, pressure tactics, and a request to change bank details or release funds.
IT support teams can use signals around an impersonated employee, unusual urgency, or a request for an MFA reset or credentials before restoring access.
Recruiting and security teams can assess remote interviews for synthetic candidates, stand-ins, manipulated video, and other indicators relevant to employment and system-access risk.
Organizations can scrutinize high-trust calls where an attacker may rely on a familiar role, cloned voice, or plausible story to redirect a payment or bypass an approval control.
Users or teams can ask Claude to check a linked image, video, or voice clip for AI generation or manipulation, then review the resulting Diopter report in the dashboard.
Diopter detects synthetic voice calls, deepfake video, AI-generated identities, and social engineering patterns. Its analysis includes audio and video manipulation signals as well as behavioral indicators in the conversation.
Yes. The product analyzes incoming audio and video streams while a call is in progress and can issue alerts as evidence develops. Its site also describes alerts with evidence and recommended actions for the security team.
It is intended for organizations where a convincing impersonation could move money, grant access, or change an identity record. Relevant users include financial services, KYC and identity verification providers, media organizations, enterprise hiring teams, help desk agents, finance staff, recruiters, and security or fraud teams.
After creating a Diopter account and connecting it in Claude, a user shares a direct HTTPS link to an image, video, or audio file and asks Claude to check it with Diopter. The connector returns a verdict, confidence score, and link to the full report; longer scans can be checked later using the request ID.
No such replacement is stated. Live-call alerts recommend independent verification or following the proper process when a request appears fraudulent or violates policy, so results should be used as decision-support signals within the organization’s controls.
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