Granola, an AI-based note-taking application, has raised $43 million in the Series B funding round, which has increased the application valuation to $250 million. The investment was co-led by NFDG, the venture firm of Nat Friedman and Daniel Gross, and joined by existing investors Lightspeed and Spark, and prominent angel investors including Guillermo Rauch (Vercel), Amjad Masad (Replit), Tobias Lütke (Shopify), and Karri Saarinen (Linear). This round raises Granola’s total amount of fundings to $67 million.
Granola has been in an unprecedented rate of growth after it started a year ago with its users increasing by approximately 10% every week. Originally created as an app for automated meeting note-taking, the app has gained momentum with users who use it for personal note-taking, using its AI tools to structure and pull out knowledge in a wider variety of information. Co-founder Chris Pedregal pointed out that users tend to have Granola open all day while using it with their daily workflows.
Coinciding with the funding announcement, Granola rolled-out new collaborative features that were meant to increase team productivity. These include the sharing of transcripts as well as notes with teammates, creating custom folders for different scenarios of collaborative use such as sales calls, customer feedback, and hiring, and provide non-Granola users with an opportunity to message these shared notes, as well as communicate with Granola’s AI.
The emphasis Granoa places on user control and personalization defines it as a unique note-taking AI tool different from such tools as Read AI, Fireflies, and Otter. Users can always edit notes meaning that Granola does not only become an app for capturing meetings but also turns into a workspace where people collaborate and store the information.
Just this month, Granola has added its AI power whereby the AI bot can be queried on all recorded meetings. Expanding on this, the app now enables the user to ask questions about particular folders and further enhance the information retrieval and context-based insights.
