"Read presents a high-risk privacy profile (79/100) comparable to Facebook/TikTok due to aggressive collection of biometric and sensitive workplace data, extensive sharing with advertising partners, and limited user control mechanisms. The service automatically collects and transfers sensitive Google Workspace and Microsoft data to third-party AI tools, captures facial expressions and behavioral analytics for scoring without explicit consent, and sells personal information and inferences to advertisers. Opt-out mechanisms are device-specific, require active intervention, and do not prevent the primary concerning practices."
read Privacy Concerns & Scorecard
Data sold to third-party advertising and marketing partners including identifiers, commercial information, internet activity, and inferences about users for targeted advertising purposes
Limited ability to prevent automatic collection of meeting data from integrated platforms; opt-out requires active intervention during or before meetings for each instance
Automatic collection and transfer of sensitive Google Workspace data (Gmail, Google Docs, Google Drive, Google Chat) and Microsoft Outlook/Calendar data to third-party AI tools without per-service consent mechanisms
Creation of inferences and derived demographics about users for behavioral targeting without explicit consent for inference-based profiling
Vague retention policies for most data types with indefinite retention for business purposes despite account deletion requests
No recommended actions at this time.
Automate your privacy
Connect your accounts to TrueTerms to automate these privacy actions and monitor policy changes.
Data Collection & Tracking
Personal Information Collected
Account creation, user identification, communication, profile management
Generate 'Read Score' engagement metrics and meeting analytics; facial recognition excluded for EU/UK users only
Meeting recording, transcription, analytics, and participant tracking
Contextual meeting analysis and AI model training
Service functionality, analytics, fraud prevention, cross-device tracking
Analytics, service improvement, campaign effectiveness measurement, targeted advertising
Targeted advertising, personalization, employment-based marketing segmentation
Billing and payment processing
Meeting participation, participant identification, outreach
Analytics, fraud prevention, service improvement
Cross-Platform Tracking
Read tracks users across the web and mobile apps through cookies, web beacons, and device identifiers to serve targeted advertisements on third-party platforms and websites. Email addresses and phone numbers are shared with advertising partners for behavioral targeting. Additionally, Read collects data from third-party services (Google Workspace, Microsoft, Slack, Zoom) and integrates it into its ecosystem for AI model training and advertising targeting.
Tracking Methods:
Cookies and Web Beacons
Read uses cookies and web beacons to track user interactions with its services and across third-party websites. These technologies enable behavioral tracking for targeted advertising and analytics.
Device Identifiers
Unique device identifiers and cookie IDs are used to track users across devices and platforms for cross-device advertising and personalization.
Hashed Email & Phone Identifiers
Email addresses and phone numbers are hashed and disclosed to advertising partners to enable behavioral targeting across web and mobile apps, linking user identities to advertising networks.
Meeting Data Capture
Automatic integration with video conferencing platforms (Google Meet, Microsoft Teams, Zoom) and productivity tools captures meeting data without per-meeting opt-in, transferring this data to Read's servers and third-party AI tools.
User Login & Account Data
Read collects account login information, profile data, and authentication credentials to track user identity and activity within the service.
AI & Data Training
read uses your content to train AI
Below is what's used and how (if at all) you can object.
What Content Is Used
Meeting Recordings (Audio & Video)
Audio and video recordings from meetings are used to train personalized AI/ML models for engagement scoring and meeting analytics. Facial expressions and verbal behavior data extracted from recordings used for model development.
Email Communications
Gmail messages, subject lines, body content, recipient and sender information transferred to third-party AI tools for training personalized AI/ML models.
Documents & Files
Google Docs content and Google Drive files transferred to third-party AI tools for training personalized models.
Calendar Events & Metadata
Google Calendar event titles, descriptions, dates, times, and guest lists; Microsoft Calendar data transferred for context in model training.
Chat Communications
Google Chat messages and metadata, as well as Slack data transferred to third-party AI tools for training.
Meeting Metadata & Characteristics
Meeting details including subject, description, location, participant names, participation data, and derived characteristics used for model training.
How to Object
- 1
Contact privacy@read.ai to request opt-out from AI model training. Policy states users can 'contact privacy@read.ai to opt-out of new/different personal data uses.' Additionally, users can disconnect Google Workspace and Microsoft integrations to prevent further data transfer to AI tools, though this does not retrieve previously transferred data.
Why We Analyzed read
TrueTerms automatically audits privacy policies and data practices using advanced machine learning to keep you informed and protected. This scorecard is based on the latest available public terms of service and privacy policies as of 2026.