User reviews of Otter.ai present a mixed picture of the transcription service's capabilities. Reviews indicate that while Otter.ai is considered easy-to-use for recording and transcription, it struggles significantly with multi-speaker conversations and produces messy transcripts that require substantial editing. Users report issues with the product not meeting advertised features, pricing transparency problems, and poor customer support, contributing to a 3.8 out of 5 rating based on 470 reviews.

Read.ai faces more severe criticism from users, with reviews showing a concerning pattern of departing customers. The service has garnered only a 1.7 out of 5 rating from 61 reviews, with users citing significant security concerns as a primary issue. Multiple reports indicate that Read.ai continues to join calls without user approval even after account deletion, raising substantial privacy and security red flags for users.

For additional information about these services, readers can explore these sources: 1, 2, 3, 4, and 5.

Otter.ai excels as a straightforward AI transcription service that captures meeting content with reliable accuracy and ease of use. Its generous free tier and simple interface make it accessible for individuals, students, and small teams who need basic note-taking functionality. However, users frequently report that transcripts can be verbose and poorly structured, making it difficult to extract actionable insights quickly.

Read.ai positions itself as a comprehensive meeting intelligence platform that goes beyond transcription to analyze engagement, sentiment, and meeting effectiveness. Its advanced analytics and multi-language support appeal to larger organizations and global teams seeking deeper insights into their meeting culture. The tool's complexity and higher price point can overwhelm users who simply want efficient meeting documentation.

Otter.ai suits individual professionals, educators, and small businesses who prioritize simplicity and cost-effectiveness in their meeting transcription needs. Read.ai targets medium to large enterprises that want to optimize meeting performance and require sophisticated analytics alongside standard transcription features. Both tools offer basic integrations with popular platforms, though neither provides the depth of workflow automation that would truly streamline post-meeting action items and follow-up tasks.

While both platforms handle transcription competently, they fall short in transforming meeting content into actionable workflows that drive productivity. Users often find themselves manually processing the generated summaries and notes rather than benefiting from seamless integration into their existing work processes. The limited automation capabilities mean meetings still require significant manual effort to convert discussions into concrete next steps.

Why users switch away from Otter.ai or Read.ai

Users switch away from Otter.ai due to transcription quality issues, particularly when dealing with complex audio situations. The service experiences accuracy problems with transcription and speaker identification when audio quality is poor or multiple speakers are present. These technical limitations can result in unreliable meeting records, which undermines the core functionality users depend on for capturing important discussions.

The structure and organization of Otter.ai's output creates usability challenges that drive users to seek alternatives. Transcripts are frequently overly verbose and lack clear structure, making it difficult for users to quickly locate key takeaways or important information from their meetings. This verbose format requires additional time to parse through content, reducing the efficiency gains users expect from an AI transcription service.

Otter.ai's meeting management system creates operational frustrations that prompt user migration. The assistant feature can spam calendar invites or join unwanted meetings when not properly configured, creating workflow disruptions and potential privacy concerns. Additionally, the free version's limitations, including a 40-minute cap on Zoom meeting transcriptions, restrict functionality for users who need longer meeting coverage without upgrading to paid plans.

Users switch away from Read.ai primarily due to its restrictive free tier limitations. The free plan allows only 5 meeting transcripts per month with basic summaries and analytics, which many users find too restrictive compared to competitors that offer more generous free usage allowances.

The complex user interface presents another barrier for users. With multiple features including notes, analytics, and search functions, the learning curve is higher than alternatives. Some users describe the interface as "confusing" and "cluttered," with one review noting it was not as time-saving as expected due to the complexity of navigating the various features.

Pricing concerns also drive users to seek alternatives, particularly for small teams and organizations requiring full functionality. The Pro plan costs $19.75 per user per month (annual billing), with Enterprise features at $29.75 per user per month, making it expensive for teams that need advanced capabilities like video playback and enhanced integrations but have limited budgets.

FAQs

Would Otter.ai work for in-person meetings? What about Read.ai?

Yes, both tools work for in-person meetings. Otter.ai can transcribe live in-person conversations via its app, and Read.ai has an iOS app that captures in-person/offline meetings with one tap.

Does either of these tools require a meeting bot to join the meeting?

Otter.ai uses an assistant that can join meetings in real time when integrating with platforms like Zoom and Teams. Read.ai does not require meeting bots - it records virtual meetings via cloud or extension, and offline audio via mobile app.

What do users say about the quality of transcriptions?

For Otter.ai, users note that accuracy can suffer with complex audio, with some reviews mentioning mistakes in transcription or speaker identification. Transcripts can also be overly verbose and lack structure, making it hard to quickly find key takeaways.

For Read.ai, users appreciate that summaries are considered "smart," capturing questions asked and topics discussed, though specific transcription accuracy feedback wasn't detailed in the available information.

Do these tools help a user follow up with action items from the meeting? How so?

Yes, both tools help with follow-up actions. Otter.ai's "OtterPilot" feature auto-generates summaries, follow-up emails, and CRM updates. Read.ai generates reports after meetings with key points and action items, and can automatically sync meeting summaries to Slack and notes to CRM systems.

Do these tools integrate with software like Hubspot, Salesforce, or Linear?

Yes, both tools offer integrations with these types of platforms. Otter.ai integrates with HubSpot and other platforms via OtterPilot, which can push notes and updates to CRM systems. Read.ai has robust integrations including HubSpot, Salesforce, Confluence, Jira, Notion, and Slack.

Another alternative: Circleback

Circleback provides best-in-class AI-powered meeting notes and automations. We support over 100 languages and automatic participant identification in both in-person and online meetings.

• Automatically-identified and assigned action items

• AI-enabled search across all meetings

• Automations with 100+ app integrations

• Industry-leading security with SOC 2 Type II, EU-U.S. Data Privacy Framework, and HIPAA compliance

• Ability to capture both online and in-person meetings with desktop and mobile apps