In 2025, UX researchers need to work fast while staying accurate. AI-powered tools and research platforms like Dovetail and Looppanel offer an exciting solution, especially with the challenges of maintaining a repository, tagging and organizing data.
In this article, we’ll do a deep dive into Dovetail AI features including Dovetail magic, Dovetail AI summary, and also answer the question: does it actually make research easier? With verified reviews from teams using Dovetail AI features, we’ll explore the possible strengths and weaknesses of Dovetail AI, and better-performing tool alternatives.
Check out a detailed review of Dovetail, and 4 cheaper tool alternatives.
What is Dovetail research repository?
The Dovetail app is a traditional user research analysis & repository tool, and a power tool for people who want to understand their users better. You can upload your recordings to Dovetail, have them transcribed and then tag your data for analysis.
What is Dovetail AI?
Dovetail has recently launched a suite of AI-powered features that transforms user data into insights “with a touch of magic”. Called Dovetail Magic, this set of AI features offers AI-powered transcription, summary of research data, automated reel generation, video highlights of key moments in customer interviews, redacting of sensitive information, analysis and repository search.
Overview: The promise vs reality of Dovetail AI
From automatic summaries to intelligent analysis, Dovetail Magic features seem to offer everything a modern research team needs. But user reviews reveal a gap between promise and reality.
When put to practical use, Dovetail AI features often create more work than they save with inaccuracies and hallucinations. Multiple attempts to regenerate or refine these summaries could yield the same unreliable results. Basic functions like searching through notes become unnecessarily complex when semantic search gets in the way of straightforward queries.
These limitations have led many teams to explore tool alternatives like Looppanel that prioritize reliable AI integration, looking for tools that truly enhance rather than complicate their research workflow.
Dovetail Features
What are the features of Dovetail?
Dovetail comes packed with tools to supercharge your user research. Here are some key features:
- Transcription: Dovetail can turn spoken words from interviews into text automatically.
- Tagging: You can label important points in your data, making them easy to find later. However, this requires a lot of labour for maintaining a consistent taxonomy across projects, to make analysis and future reviews easier.
- Analysis tools: Dovetail AI helps you spot patterns and trends in your data.
- Video highlights: You can create short clips from long user interviews to highlight key moments.
- Sentiment analysis: Dovetail can figure out if user feedback is positive, negative, or neutral.
- Collaboration tools: Teams can work together, leaving comments and sharing insights.
- Report creation: Dovetail helps you make clear, visually appealing reports to share your findings.
- Integration: Dovetail works with other tools you might use, like Zoom for interviews or Slack for team chats.
What are the AI features in Dovetail?
Let's dive deeper into each of Dovetail's AI features.
Magic Summarize
It can summarize long documents, interviews, or even groups of comments. You can choose how detailed you want the summary to be. It spots key themes and important quotes, saving you hours of reading.
Magic Transcribe
The transcription feature handles multiple speakers and different accents. However, with a 90% accuracy rate, it falls short of competitors like Looppanel with 95%+ accuracy.
Magic Reels
Dovetail AI’s Reels feature scans through long videos and picks out important moments. You can easily share these compilations of video highlight clips with your team or put them in presentations.
Magic Highlight
Magic Highlight reads through your research and highlights key points automatically. It can spot important themes, problems users mention, or positive feedback.
If you're looking through hundreds of survey responses, Magic Highlight can help you quickly see what topics come up most often.
Magic Redact
This Dovetail AI feature scans your data for personal or sensitive information. It can spot things like names, emails, phone numbers, or other private details. You can set it to look for specific types of information you want to keep private.
If you're sharing user feedback with your team, Magic Redact helps ensure you're not accidentally sharing users' private details.
Magic Search
You can search across all your research by topic, ask questions, and get answers based on your repository data.
Channels
Channels automatically sort your research based on rules you set. New data gets filed in the right place without you having to do it manually. You can have channels for different projects, topics, or types of feedback.
Magic Cluster
It groups similar ideas or feedback together, even if they're worded differently, helping you see trends or common themes in your data. It can help you notice issues or ideas you might have missed.
Dovetail AI Review
Read: Dovetail User Research: A Complete Review + Top 3 Alternatives
What Dovetail AI can do
Dovetail features start with the basics—-transcription in 28 languages and a comprehensive tagging system. Through dovetail.ai, teams can analyze their research across different views like Trello boards, canvases, and tables. Dovetail analysis capabilities also allow filtering and searching across projects using tags.
For teams that have time and resources to invest in detailed organization, these tools can provide a structured approach to research management.
Where Dovetail AI falls short
While Dovetail offers useful basic features for managing research projects, its AI capabilities present several significant challenges.
The Dovetail.ai summary tool has been reported to produce unreliable results that require extensive verification. Tests show that while it can identify basic elements like warm-up questions and simple tasks, it often introduces fabricated information and misattributes statements.
The Dovetail AI summary feature also has shown particular weakness in accuracy and consistency. The tool struggles with participant identification, often mixing up roles and using inconsistent terminology throughout summaries. Even using different summary options or regenerating results doesn't improve the output quality. Most concerning is that the AI can introduce completely fictional elements into summaries, making them unsuitable for professional research use without thorough human verification.
Beyond AI issues, the platform's heavy reliance on taxonomies and tagging creates significant overhead for teams. The semantic search functionality, while advanced in theory, often complicates simple search tasks. Users report difficulty finding specific information as the AI-powered search sometimes interferes with basic keyword searches. This combination of unreliable AI features and complex organizational requirements makes Dovetail UX particularly challenging for large organizations or teams needing quick, accurate insights.
Dovetail AI Alternative: Looppanel
Looppanel is a UX research analysis & repository solution for the modern UX team. Looppanel helps you analyze research data 10x faster, centralize feedback in one searchable hub, and surface insights in seconds.
Teams like PandaDoc, Thumbtack, and Beigene use Looppanel to make faster, insight-backed product decisions.
Looppanel's features include:
- 95% accurate transcripts (across accents and regions)
- 10x faster analysis via auto-tagging, automatic notes, and more
- Smart search for insights and quotes across your data
- Shareable video clips and insights (you can embed these into Jira tickets, Notion, etc.)
- Analysis across calls by question or tag
Here are 3 reasons why Looppanel offers a better alternative to Dovetail.
Superior transcription
When comparing transcription capabilities between the platforms, Looppanel demonstrates significantly higher accuracy. In controlled tests using the same source material, Looppanel produced fewer errors and more readable transcripts. While Dovetail tends to fragment speaker text into smaller, disconnected chunks, Looppanel maintains natural speech flow, making transcripts easier to read and analyze.
Thoughtful AI integration
Rather than simply adding AI features, Looppanel builds them into the core research workflow. The platform's AI capabilities focus on three key principles: traceability of all AI outputs back to source material, user control over AI suggestions, and consistently high-quality results. This approach creates a trustworthy system where AI truly accelerates research work instead of creating extra verification tasks.
Inclusive collaboration model
Unlike Dovetail's per-user pricing that can quickly become costly as teams grow, Looppanel's Pro plan includes unlimited collaborators. While there are some limits on annual file imports, this model makes it more feasible for entire organizations to engage with research insights. Teams can freely include stakeholders from product, design, and other departments without worrying about additional seat costs.
Efficiency gains
While traditional Dovetail analysis requires extensive manual work, Looppanel offers genuine automation. Teams report analyzing data up to 10 times faster through auto-tagging and automatic notes generation. Unlike Dovetail thematic analysis, which demands constant taxonomy maintenance, Looppanel's smart search works without extensive manual tagging.
Cost-effectiveness
Recent changes in Dovetail UX pricing have made enterprise plans increasingly expensive, often reaching $21,000 or more. The per-user pricing model can limit collaboration as teams grow. Looppanel's Pro plan includes unlimited collaborators, though it does limit annual file imports.
Looppanel’s users rave about all the time Looppanel has saved them in analysis. If you'd like to see it for yourself, request a free demo here.
Frequently Asked Questions (FAQs)
What AI does Dovetail use?
Dovetail uses advanced AI powered by Amazon Web Services (AWS). Their AI learns from your research to get better at helping you, but it doesn't use your data to help other companies.
What are the objectives of Dovetail?
Dovetail aims to centralize user research data and make insights accessible across organizations. Its primary goals include providing a structured approach to research organization, enabling collaborative analysis, and helping teams maintain a comprehensive record of user insights.
What is the Dovetail app used for?
Dovetail serves as a centralized platform for user research management, where teams can store, transcribe, and analyze their research data. The app helps organize interview recordings, survey responses, and research artifacts in one searchable location, with features for transcription across 28 languages and various analysis views including Trello boards, canvases, and tables.
How does Dovetail help product managers master continuous product discovery?
Product managers use Dovetail to organize and analyze user feedback across multiple research projects. The platform offers tools for processing interviews, creating video clips of key moments, and organizing findings through a tagging system. However, the heavy reliance on manual tagging and complex taxonomies can slow down the discovery process, especially for teams needing quick insights.
What is Dovetail software used for?
Dovetail software functions as a research repository and analysis platform, designed to help teams manage qualitative research data. It provides tools for transcribing interviews, organizing research findings through tagging taxonomies, and analyzing data across different visualization formats. Teams primarily use it for storing and organizing research artifacts, though the effectiveness depends heavily on their ability to maintain consistent tagging practices.
Is Dovetail AI legit?
While Dovetail AI is a legitimate offering from an established UX research platform, its performance varies significantly. The AI features are real but often fall short of user expectations, particularly in areas like summary generation and pattern recognition. Teams should approach these features with realistic expectations and plan for manual verification of AI-generated outputs.
What does Dovetail company do?
Dovetail is a company that develops and maintains a user research platform focused on helping teams store, analyze, and share research insights. They provide tools for research management, including transcription services, tagging systems, and basic AI features. The company serves various organizations, from small research teams to large enterprises, though their pricing structure tends to target larger organizations with significant research budgets.
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