AI-Powered Revenue is Here

1. DHDiana Hu0:00

   [upbeat music] I'm excited today to welcome the founders of Letter.ai, who are announcing their 40 million Series B round. Here is Ali and Armen. Tell us, uh, what Letter.ai is.

2. AAAli Akhtar0:18

   Hey, Diana, nice to be here. Uh, Letter.ai is an AI-native enablement platform, which means we help revenue teams ramp up more quickly with personalized training, coaching, and also deliver content to engage buyers, ultimately to accelerate the deal cycle.

3. DHDiana Hu0:33

   Who are some of your top customers that are live right now?

4. AAAli Akhtar0:36

   Yeah. We have a, a healthy mix of customers across large enterprises, like Lenovo, uh, Adobe, Novo Nordisk, uh, as well as fast-growing startups like Plaid and Kong.

5. DHDiana Hu0:47

   That's a pretty good list. What are some of the key use cases that they, that they handle with you?

6. AAAli Akhtar0:51

   Across the spectrum. So, uh, first and foremost, onboarding new team members, making sure they're productive in about half the time as they were prior to Letter. Uh, second is through the sales cycle, as questions come up, as customers request content, being able to leverage AI to, uh, be able to curate personalized content to be able to share with the prospect at just the right time. We have an AI role-playing simulation capability as well, so you can practice before you go into a call with an actual buyer. Uh, and a whole host of new capabilities we're launching as well.

7. DHDiana Hu1:21

   Hmm. Sort of a simulation for sales folks before they actually do the actual sale conversation, right?

8. AAAli Akhtar1:28

   Exactly. You don't wanna fail in a live conversation, especially with a high-stakes prospect, and so Letter allows you to practice many times before you ever go into that conversation.

9. DHDiana Hu1:37

   So the interesting thing is, you guys were here doing YC not too long ago, and you already raised a Series B. You were here at YC just two and a half years ago. Uh, but not many people know that when you went through YC, you were a very different company-

10. AAAli Akhtar1:56

    Yes

11. DHDiana Hu1:57

    ... and had a different name. You were Tractatus.

12. AAAli Akhtar2:00

    Yes.

13. DHDiana Hu2:00

    What was then... What did you learn that that idea didn't work? And tell us a bit about that initial journey.

14. AAAli Akhtar2:06

    Yeah, absolutely. Arm- Armen, you wanna tell the story of Tractatus? [chuckles]

15. AFArmen Forget2:09

    Uh, yeah, we were basically doing, uh, developer tools for generative AI, and through the process of Y Combinator, um, we learned very quickly that this was, uh, probably not a great idea. Uh, the field was getting very saturated. Uh, we were trying to sell SaaS tools to developers who wanted to write Python code, and, uh, they would, uh, very quickly do prototyping in our platform, and then they would just go build it themselves, and so it wasn't very sticky. And, uh, you know, we changed the name as well to make it-

16. DHDiana Hu2:40

    [chuckles]

17. AFArmen Forget2:40

    ... a little bit more, more mem- memorable.

18. DHDiana Hu2:42

    What was interesting is you landed on this idea, which, at the surface, seems like it should be very crowded or very old school. There's just so many tools in sales. Uh, but Ali, you figured out s- a unique insight during the batch, and what was that, and what happened? Because the impressive thing is, you were actually able to close Lenovo as a customer in the batch-

19. AAAli Akhtar3:06

    Yeah

20. DHDiana Hu3:06

    ... which is very rare.

21. AAAli Akhtar3:08

    Yeah. Yeah, it was, it was quite incredible. And for us, y- you know, the big insight was, uh, it really driven by personal experience. So when I was at Samsara and at Project 44, I had used some of the legacy enablement stack. Uh, I remember every single week I would get pinged by a seller at Samsara. There, I was director of engineering for machine learning. Uh, nothing, no involvement with the sales org by role, but I'd get pinged by sellers asking: "How does this product work? Can you tell me about these features? Can you come and give a talk on it?" And I remember saying, "Hey, why don't you go find all the content we put together, all the learning we put together in our legacy enablement tool?" And the sellers would say, "I can't find anything in there. I barely log in." Uh, and so, uh, you know, that was kind of light bulb moment number one, is there's this really expensive tool, which by the way, I couldn't even get a license to-

22. DHDiana Hu3:57

    Mm

23. AAAli Akhtar3:57

    ... uh, because it was so expensive, uh, that it's getting very low adoption. Uh, and the second kind of insight here was, um, a lot of times to get leverage and adoption out of enablement tools, you really need to throw a lot of humans at it, and so humans need to be out there curating content, building content, building training. And we found that with AI, you could actually tap into existing sources of knowledge and accelerate the process of highly personalized content development, and speed is what matters in today's day and age for, you know, uh, high-velocity sales organizations. Uh, and so we thought, "Let's just rethink this entire set of use cases using AI," and that's how Letter came to be. Uh, and Lenovo actually started through, you know, uh, someone I knew there, uh, from a previous job, uh, who, you know, was kind enough to see what we were trying to do, and it lit a light bulb in his mind, and he connected us to the right folks within sales. And once they saw what we were building... And we took a few steps to make sure we were enterprise-ready early on in the journey. Uh, that helped us unlock, uh, you know, a fairly substantial deal with them that's since grown 10x, uh, over the course of the past, uh, two years.

24. DHDiana Hu5:03

    So that's kinda interesting. So you're telling me there's this gap between basically the product engineering team that's shipping things very fast, especially now-

25. AAAli Akhtar5:13

    Yeah

26. DHDiana Hu5:13

    ... in the age of intelligence, product velocity is very fast, and then there's this gap of translating what is in the product to the sales team-

27. AAAli Akhtar5:23

    Yeah

28. DHDiana Hu5:23

    ... who's not technical, can't necessarily read the code. But now, with AI, you basically supercharge them and automatically produce all the features and, and, and sales materials for the team to go at it.

29. AAAli Akhtar5:38

    Yeah.

30. DHDiana Hu5:38

    So can you tell us about what are some of these results with some of your customers? Because you were telling me about, um, this story of a customer that just acquired a company, and-

Episode duration: 10:20