Using Dovetail AI
Streamline your process with Dovetail AI. Leverage these AI features to speed up sentiment analysis in your notes, clustering and uncovering themes from highlights, and summarizing notes and insights.
Table of contents
Automatic sentiment analysis of notes
Automatic sentiment analysis uses AI to analyze for general or targeted sentiment within your notes. By default, it is conducted on the whole note and can be run on part of a note by selecting a section of text. Sentences featuring strong sentiments will be highlighted and tagged as Positive or Negative.
Learn more about automatic sentiment analysis →
Thematic clustering of highlights
Use AI to cluster your highlights into groups based on thematic similarities in a canvas layout. Themes are created from the content of your highlights, not the tags or titles. After creating clusters, the AI will also generate titles for each group.
Learn more about clustering highlights into themes with AI →
Summarizing key points in notes and insights
Save time identifying key themes in interviews, documents, or customer feedback, and turn them into valuable insights using AI. Add data to your notes and insights - including content like PDFs, reels, and transcripts - and we'll automatically generate a summary of the key points.
Learn more about creating summaries of your data with Dovetail AI →
FAQs
Why should I use Dovetail’s AI features over ChatGPT?
Dovetail’s tailored AI infrastructure means that your data won’t be used to train models for Dovetail or other customers—it’s fully secure. We select a model for the task at hand—whether that’s summarizing an insight or clustering highlights by theme. While ChatGPT enforces character limits, tailored infrastructure means that our AI features can handle whole transcripts and multiple highlights simultaneously.
Using Dovetail’s AI features ensures that all your customer data is in one place, so you don’t need to copy and paste data between tools and risk human error.
Will my data be secure if I use Dovetail AI?
We understand research data can contain lots of personal and commercially sensitive information, and participants trust you to keep it safe. That’s why we are committed to keeping this data secure and confidential.
Unlike tools like ChatGPT—which may use your data to train their models—we use tailored processing infrastructure on AWS, meaning your data remains your own. We deploy all our models in the same place it’s already stored. The request is sent to the model, and the response is returned. Models aren’t learning from your data.
You can read more about our data handling practices in our MSA (see in particular section 4, section 6, and section 11), our privacy policy, data processing agreement, and Dovetail trust center.
How is the model trained and deployed?
Dovetail uses a variety of market-leading LLMs. No customer data is used to improve or train our model—all training occurs before the models are deployed. Our models are constantly updated and improved to ensure you get the best experience.
Which Dovetail features use ML vs. generative AI?
Depending on the task, Dovetail’s AI features use machine learning (ML) or a combination of both ML and generative AI.
ML powers Dovetail’s transcription process. It allows us to identify positive and negative sentiments in transcripts and identify and blur faces to protect your users’ privacy. It’s also used to identify and cluster highlights by theme in canvas.
We use generative AI to summarize notes and insights that make it easy for you to keep stakeholders up-to-date. We also use generative AI to label your themes in canvas.
What is the difference between ML and generative AI?
We use a combination of generative AI and machine learning (ML) to power our AI features. While both are subsets of AI, put simply, ML uncovers and predicts patterns, and generative AI creates new content.
ML uses models and algorithms to do heavy lifting in making sense of large data sets. It’s able to find patterns among lots of data quickly, making it valuable for things like facial recognition and grouping themes.
Generative AI applies large language models and algorithms to create content. It taps into large content repositories, making it useful for generating summaries and answering questions.
Can I turn off Dovetail's AI features?
AI is foundational to many of Dovetail’s core features, including transcription and sentiment analysis, which means deactivating it for specific workspaces is not possible at this time.
Product specific terms
For more on Dovetail AI, check out our product-specific terms here.
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