AGAT Software Announces the Launch of the Recording AI Compliance Analysis Capabilities for All the Leading Vendors in the Unified Communications Software Industry: Webex Meetings, Zoom and Microsoft Teams

AGAT, a market-leader in Security and Compliance solutions for Unified Communications (UC) announces the launch of the Recording AI Compliance Analysis capabilities for all Webex Meetings, Zoom and Microsoft Teams.

AGAT Software is pushing the limits and setting higher standards for what regulation technology for those such as FINRA, GDPR, HIPAA &  MiFID II.

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In a world where video conferencing is becoming more common than the regular face to face and audio calls are replacing chat or emails, SphereShield by AGAT is coming to deliver advanced yet intuitive solutions for recording compliance and deep analysis.

In a nutshell, AGAT is bringing audio and video (including screen sharing) analysis for DLP and eDiscovery needs, meaning that companies can have a precise written record of who said what at a video conference and which content was shared on the screen.

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The possibilities include the following

• Transcribe all recorded meetings audio:
  Support audio transcription for 70 languages.
  Automatic language detection and Speaker enumeration: which speaker spoke which words and when.
• Search meeting content using eDiscovery
  Dates, Attendees names and type (internal/external), Text, Audio, Video, Keywords, Labels, Names, Etc.
• Inspect meeting audio and video for DLP policy compliance
• Smart DLP incidents with link to video and transcript time of violation
• Ethical wall – validate meeting attendee using configurable compliance policies
• Option to store video archiving on prem or on VPS
• Use SphereShield built-in DLP engine or integrate with leading vendors
  Works with Symantec, McAfee, Google, GTB and Forcepoint.
• Advanced AI and NLP Analytics for detection of
  Named entities (products, countries, etc.).
  Emotion detection- Extract from what’s being said and voice tonality emotions such as joy, sadness, anger, or fear.
  Sentiments detection – positive / negative.
  Automatic video scenes generation.
  Labels and Keywords.

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