Granola raises $43M Series B to build AI-powered team intelligence layer on top of meetings

our first guest into the studio. Welcome to the show. How are you doing? It's Granola time. What's happening? Congratulations. How you doing? We're doing great. Uh, would you mind introducing yourself and the company a little bit? Totally. My name is Chris. I'm the co-founder CEO of Granola.

Um, how much you wanted me to tell about it? Tell us everything. Yeah. I mean specifically the evolution specifically the evolution of the product because I know people think notetaking but you're doing a lot more. Uh so give us kind of the what was the initial pro uh the initial uh minimum viable product.

What's the product today? Where is it going? Totally. So uh we launched Granola a little under a year ago and the idea was the best way to take notes during meetings and to do that in collaboration with AI. So, it's an app that lives on your Mac. It looks a lot like Apple Notes.

You can take notes however you want, but it listens to the conversation in the background and when the meeting's over, it'll like rewrite your notes to like flesh them out to make them great. Um, yeah. And that that's the basic product. We tried to keep it super simple, uh, really minimal.

And, um, I mean, I think I think that design resonated. I think we can talk about that. But there I think there are a few things about the way we built that that people really liked.

And then I think what we noticed happening was that once you start using granola, what happens is you have a meeting and like a notification pops up saying, "Hey, you this meeting starting. Do you want to use granola for it?

" And once you start using granola for lots of meetings, it kind of becomes this like searchable second brain repository thing. Like you can kind of be like, "Hey, what did that person say? " And you kind of turn to it and we notice lots of users doing that.

And then kind of the evolution like what we launched today is now you can do that across your team.

So like now you can you can chat we added a bunch of support for these great reasoning models and you can chat ac across meetings across your whole team and ask questions and it's a stepping stone towards like the bigger vision of where we're going. Yeah. But yeah. Uh tell me about search.

Are you stuffing every granola uh note into a vector database or are you just doing a huge context window? What are the different strategies to actually surface insights? It I mean it's it's definitely evolving.

What what we found is like rag or like stuffing it into a vector database is really good for certain types of like information lookup like search. What what it's what it is terrible at is basically if you ask questions like hey um like coach me like how how could I be better in my one-on- ones, right?

or um when let's say you're trying to sell something it's like hey when I get this type of question like how good are my answers and how does that compare to the answers that other folks on my team give like it completely rag completely breaks with that and what we find is people turn to granola to ask a lot of these kind of analysis type questions like hey what are the biggest burning fires right that I should be focused on or something like that and um rag's not suitable so we actually make a lot of use of stuffing these massive context windows with the right with the right transcripts and and not what's the favorite context window to stuff?

Um I know Gemini's got a big one, but they all have trade-offs, but llamas do the bigger scare you. No, no, the big ones scare me. Uh open AI's context windows. Perfect. Um we just we just today starting today we let users choose. Before that it was, you know, we do we have everyone's going model agnostic.

This is a trend, right? Yeah. I mean, wind surf is model agnostic now. Who else were you saying? Uh Harvey just went model agnostic. Uh this seems to be the trend. Really? You're drinking the commoditization Kool-Aid. Yeah.

The the product person in me feel I have mixed feelings about about surfacing it to the user because it's like one more thing a user has to think about and your average person shouldn't have to think about. We should do the best thing. So it defaults to auto.

So we try to choose the right model which for a lot of it is is like Sonic Cloud 3. 7 like the reasoning mode of it because we find that that for the type of queries that we're getting is it works the best. But you know if you're a power user now you can choose Gemini 03 like whatever you want. Cool.

Uh I got to ask uh what was your reaction to notion's launch yesterday? Uh many people said uh it was a granola clone. Do we have a shots fired? Yeah, we need like a shots fired sound effect. But, um, yeah, I'm curious to get I'm curious to get, you know, your reaction to it.

Um, I'm sure it's not even the first time that somebody's taken a little inspiration from you guys over the last year. I mean, I it feels like it means we're doing something right is is my first reaction. Like I it'd be easier if I didn't like Notion. We really like Notion, right? Like we think they're great.

Like Ivan actually DM' me on Twitter letting me know it was coming beforehand, you know, as in like, hey, wow, that's really sweet. It's really cool, you know? like we respect you. I hope this leads to us pushing each other to build better products for people. So like I I like them.

Um what it means for I mean I think the world changed overnight with AI and we're like 2% of the way there figuring out like what does that mean in terms of products and tools and there's just a ton to build, right? I feel like transcription from the beginning has always been a a commodity, right?

Everything is going to have transcription. So I think the question is how do you go from what we have today to like a true AI assistant that kind of understands you and helps you like be a thought partner and do most of the work you want to do. Yeah.

It feels like there's like three different like approaches to building a new AI enabled note-taking app or something like that in this world. It's like uh green field project with a startup that has a fresh clean slate like you guys.

There's notion which is like a well-funded scaled company but still in founder mode can still like we saw this with like Figma roll a bunch of new features in move still pretty agile compete and then there's the hyperscalers which are just like we have a monopoly and yeah it might take us 10 years to add this feature but you're probably still going to be using an iPhone so uh yeah expect Apple notes to get an update in 2035 or something like that but I'm interested to know kind of like do you see the market that way and and how are you thinking about uh the broader competition?

Because I imagine that if you just look at the overall like people taking notes, Apple notes is probably still the number one product or something like that or notepad. Um and so maybe that's the real opportunity and you and notion can both win. Yeah, I think it's an interesting question. it. Okay.

So, one one angle is like I think we underestimate ju you remember when mobile came out and everyone tried to port websites to to mobile to the iPhone and like it took us a little while to figure out that that doesn't work and that mobile apps should look really different. Yeah.

The jump from mobile to from web to mobile is a fraction of the jump of like prei to post AAI. So like I really think the future's going to look very different. I think and in a in a very different future. I think the the products that are kind of like invented in that new medium tend to do better.

You know, that doesn't doesn't mean like the the massive companies won't be able to add really cool AI features, but if you think about the AI features you use on a daily basis, how many of them were launched by startups, you know, that that came out in the last two years versus how many of them were launched by big companies?

Like it's like an interesting assessment to do. So, like I see it like there's a ton of opportunity. I really think like when Sam and I started Granola, it wasn't a our vision was never meeting notes.

Our vision was to be like a tool for thought that is contextually aware and AI powered like from the you know you can you can see the stuff that we wrote before launch and meeting notes just turned out to be a freaking awesome wedge. Like we thought it would be a good wedge. Turns out it's an amazing wedge.

Way better than we thought because there's like so much information in in our conversations that we don't is there also like a viral loop there where people are sharing their notes with each other on boarding I imagined. Yeah.

I mean like basically the granola product is nothing like there's no growth stuff built in like until today there's it was like single player product. Oh really? It's just something really Yeah. Yeah. There's something super inherent about the information in meetings and wanting to share that right.

So it's it's all been like word of mouth until now. Yeah. I think. But I imagine I I if I take notes in a meeting, I could share a a static link and we're not multiplayer in that, but I could share my notes and then I'm seeing granola. com and I'm just That's true. Yeah. Yeah.

You can you can share a link and and now you can even you can like put a bunch of meetings together in a folder. You can share folder and someone who doesn't have granola can now see those and you know if they log in and then um granola. ai. Sorry, I got the domain not wrong. Do you have I'm curious.

Do you have a do you have a strong thesis around agents? You know, I can imagine at some point companies have agents that are calling people and companies want to kind of understand the the context of those conversations and what what happened what what kind of ne next steps need to take place.

Is that something that would live in granola or is that more at the CRM level? What what what's your theory there? Oh man. I I mean I I think the you mentioned CRM.

I think the product categories that we've had for the last 20 years, whether it's like okay, you have like a wiki company, you have a CRM, you have like your docs company or I think those are all going to get redrawn because I think in in an AI world, it's it's all about context, right?

And then how do you make use of that context to to do work? So yeah. Yeah, if you have agents calling people, I don't think that's very different from other folks on your team calling people. And then how do you make that context useful? I think that could live in granola.

I also think agents are just one of those terms or I think we throw it around now, but we don't really there's probably like 15 different things that today we're calling agents that are going to be their own separate things in the future. Um, and it'll be really interesting to see how how that evolves.

So, I got a real time uh follow-up question from our mutual friend Michael at Lightseed who uh was in is in the new round, but he asked uh uh is there an opportunity around agents to take uh action uh based on meeting notes, right?

Because in a beautiful world, humans get together, they have a conversation, you figure out next steps, and then things immediately start to happen uh autonomously. 100% like 100 like that.

That's the whole future of granola is basically like how do we use this context for meeting notes but also in the future email slack you know Google docs whatever to help you do work and like our vision for granola is like AI should do all the busy work for you right and you should only be left with the judgment so you can imagine a world you come out of a few meetings it's already kind of done all the the postmeating work or suggestions and all you have to do is kind of be like h a little bit more this way or yeah that looks good yep yep yep yep do that and then move on to your Next thing, what's the use of the funds?

43 million big series B. Uh is LLM inference a material cost to your business right now? Is it just hiring more engineers, product people? Doesn't seem like you're going to be training foundation models if you're moving to uh model agnostic, but what's the use of funds look like over the next 12 to 18 months?

Yeah, I mean I like I said, I think there's a we're like in this pivotal moment in history to build the future tooling of work and it's a big vision and we need to hire the best people in the world to go out and build that and there's a just a ton to build. So that's the primary use. Um LLM inference is it costs money.

Transcription actually costs more. So we we transcribe millions of minutes millions of minutes a day right now. So that actually does cost some money but people also pay for granola. So like that the funds are really like can we go after this massive vision? That makes a ton of sense.

Uh and what's uh what's what's the uh dispersion of the team going to look like over the next couple years? I know you're in London now. You are an American though. Yeah. Uh what what what does it look like? Yeah. I mean I think we So when we launched Can we were four people, we're 18 people now.

We're still tiny, right? Uh but we got a great group of people here. So, we're definitely going to grow um the team in London because I think there's a lot of talent, but our ambitions are global, right? So, we're definitely going to be opening up more offices probably in the US, probably multiple in the US.

Um but all that's TBD. Awesome. Very cool. Thank you so much for the milestone. Congratulations and love to see Natt Friedman making some money. Size Lord, we love having Chris. Yeah, he's great. Thank you so much, guys. We'll talk to you soon. Have a good Uh, quickly let me tell you about public.

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