The world of AI tools for GTM is crowded, to say the least. It seems like there are point solutions for everything — an AI agentic solution for cold-calling, another for enrichment, another for research, another for upsell, another for giving executives visibility. For investors and revenue leaders alike, it can be exhausting to parse through all the options.
The founders of Clarify had a much bigger vision from the beginning, which is why I was drawn to them and decided to invest in both their Seed and Series A (which was announced today!). In this conversation with co-founders Patrick Thompson and Austin Hay, I unpack their idea of “autonomous go-to-market” and their vision for what “excellence” looks like for founder-led sales and early-stage revenue teams in the genAI era. We tackle questions such as:
What should founders expect from their CRM?
What does founder-led sales look like nowadays?
What should your GTM tech stack look like?
Check out the audio version or the refined transcript below. Let’s dive in!
Allison Pickens: Patrick and Austin, thank you so much for joining us today.
Patrick Thompson: Excited to be here.
Austin Hay: Thanks so much for having us, Allison.
AP: I'm excited for this conversation. I know you all have thought so deeply about the world of CRM for a long time. To kick things off, can you talk a little bit about why you started Clarify?
PT: Austin and I connected back in May of 2023. I was still at Amplitude. Austin was a very early adopter of Iteratively, a CDP that got acquired by Amplitude that I was one of the co-founders of. We connected to talk a little bit about what was going on in the world. One of the issues that we both saw was around the broken promises that a lot of the go-to-market tooling had.
We spent a ton of time doing customer discovery and what we realized is that we really just needed to rethink what GTM tooling looked like in the context of an AI-native world. And that's how the Clarify story culminated. We ended up doing about six months of customer discovery and kicked things off in January of 2024.
AP: Can you talk a bit about your vision for the CRM? In particular, I know that there's a term that you've coined called “autonomous CRM.” What is that exactly?
AH: The autonomous CRM is something that has lived in our brains for a long time, but it's only really manifested itself in this word in probably the last quarter or two. To take a step back, when you think about legacy CRMs, they're the exact opposite of autonomous. They are very manual, they're administrative, and that actually goes all the way back to the founding of the CRM. It was literally just a database to take structured data from your brain and allow CROs to manage their sales pipeline and sales process.
The autonomous CRM though, is designed to manage itself. For people who have used Salesforce or HubSpot or any of the major CRMs out there, they're very accustomed to this understanding that when you buy a CRM, you're also buying management and maintenance of that CRM for a pretty long time afterwards. And as we started to build Clarify, we really set out to create this dream where sellers could just show up at their job and start building relationships.
One of our first — not marketing messages; I'd call it one of our central promises — was, what if you could spend your entire day building relationships instead of managing the CRM? Because especially as early founders out there might know, you are the administrator as well as the seller. And so when you use a tool like HubSpot or Salesforce or any of these other solutions out there, you have to do that administrative work yourself. And many people can't actually afford to hire folks to help them. So I think over time, as we've layered on new product features to Clarify, what we've come to understand is that we actually are building a CRM that works for you. It's a CRM that manages itself. It's a CRM that is an agent in and of itself.
It has the ability to self-manage. It has the ability to help you follow up with calls. It has the ability to remind you of the emails that you're supposed to follow up with. Pat and I laugh about this every single day, but we really are designing Clarify for ourselves. And that means we're designing it for other people as well. We'll get through a really long busy work day. We've had six, seven, eight customer calls. You have six, seven emails to follow up with, the people from yesterday, the people from before, and it becomes really challenging.
And so some of the best sellers in the world spend two to three hours on average a day managing that process manually. And we are really trying to be a CRM that does that for you automatically. So that's where the word autonomous comes from.
Related to this idea of autonomy is this idea of background intelligence, or ambient intelligence. Rather than making this tool an AI widget that you slap on top, we're really trying to make Clarify actually natively intelligent. So it's reading your emails, it's looking at your calendar meetings, it's listening to your calls and it's understanding ambiently what should be going on. And that's what eventually makes it autonomous is its ability to act for you. It actually understands what's happening behind the scenes.
AP: I know there's a related term that you talk about called autonomous go-to-market. Tell me how that's related to autonomous CRM.
AH: I think people are feeling this right now. If you back way up, it's like the early 2000s were the era where the Salesforce solution came to market at the same time that people were figuring out B2B online sales. You have a database, you enter your mindshare into this database, you manage your pipeline, you're doing things manually.
I have a call, I enter a task. I send an email, I enter a task. At the end of the week, I sit down with my sellers and I look at my pipeline. We review things and close things. And so the shape of what the sales process looks like today for most modern sellers was obviously developed long ago, but especially in a CRM in the early 2000s. The only thing that really changed from 2010 to even 2022, was that you add a bunch of tools that start to take away some of that manual effort and also help you scale massively.
So, on the manual effort piece, there are integrations with Gmail that pull stuff in for you. On the scale piece, there are solutions like Outreach that help you email thousands of people as opposed to ten people a day. So we've seen automation help with scale and also with performing the work to be done. But what we're converging on right now is this situation where you actually don't have to use engineers or solutions engineers or rev tech professionals. You can actually use the machine itself to power your entire go-to-market motion.
There's this term that's floating around the internet called "the go-to-market engineer." It's basically this person that works all day in tools, sending emails and responding to emails and scheduling lead calls. And oftentimes, that person is also the seller and maybe also is the founder. Especially for a lot of young companies right now, the founder is the one setting up the Zapier workflows with Clay and outbounding tools and prospecting tools.
They're basically building their entire machinery around a CRM to support themselves in having sales deals. And that's really what's meant with the autonomous go-to market motion. It's this idea that we're converging on a point where today humans have to intervene and manage these machines and connect them all. But pretty soon, we may reach a point where machines themselves help you build your entire go-to-market motion. Especially with some of the trends that are coming out of AI and MCP. We will get a point where tools can talk to one another. And so you can imagine, Patrick and I could probably be a pretty vicious duo. I'm basically managing Clarify to help schedule 100 calls for us and then the next week we go take those 100 calls. Whereas you back up five years, that would never have been possible without a team of five to seven SDRs.
AP: People are talking about this vision of the billion-dollar company that will be built by one person, or maybe in your case a couple of people.
AH: Two people—me and Pat.
AP: Two people. It sounds like Clarify could be core to achieving that vision.
AH: Totally.
AP: Did you ever think about calling Clarify an “AI go-to-market engineer” instead of calling it a CRM — rebranding the category entirely? I’m just curious.
AH: We've talked a lot about category creation. Well, actually when Pat and I first met in New York, we were talking about what do you call a CDP and a CRM? It's like a different architecture underneath — do we mint a new coin?
Category creation is really hard, especially when you're a young startup. I think it gets easier when you have some clout and recognition to start coining terms around specific waves that are happening. But regardless of what you call it, the wave is happening underneath all this. Something that we think a lot about is this idea of just using the AI term, getting drowned out by the AI term. And even with agentic experiences, do we lean too hard into that marketing motion or not? And I think where we ultimately came to conclusion is that you obviously want to stand out.
But also, when we really thought about what's happening behind the scene, it's not like when you log into Clarify, you have to go set up ten different agents to run for you. It just does it by itself. So, it's both AI, it is agentic, but most importantly, it's automatic. It's autonomous. It's working without you having to really take any action. And I would call out that this is again a very big deviation from the way that a lot of revenue operators work.
Typically, when you log into a legacy tool, you're used to setting up and configuring tons of things for it to even work remotely the way that you want. For anybody out here using Salesforce, you've got to configure opportunity fields the way that you want. You've got to configure workflows to turn leads into contacts to then assign to an opportunity.
As your go-to-market motion expands and matures, you have to put in energy and investment to make that work. And I think the idea with Clarify and the dream of what we built is that you don't actually have to make that investment. It happens automatically for you.
AP: I'm wondering how the roles at a startup are changing as a result of companies using Clarify. Everyone has historically talked about founder-led sales from zero to a million in ARR. That's the classic rule of thumb, but I am noticing founders getting even farther than a million in ARR without hiring a salesperson. So I'm curious to know, are you noticing founders delaying those hires when they use your product? Are they reconsidering hiring a RevOps person? How's the structure of their teams changing?
PT: I specifically talk about founders finding the ramp is much quicker now. What took zero to one, a year or two to achieve (even longer potentially for startups) is happening much, much quicker now with AI. Just as it's a lot easier to build products now with AI as well. And so people can get farther but also accelerate growth at a much higher velocity than what was typically possible. And a founder-led sales motion is still super valuable. But also when it comes to not hiring a person, you're hiring tooling or hiring an agent to be able to automate some of these tasks that typically you would've had to hire people for. Obviously hiring is costly, takes a lot of time if you always have mis-hires.
That's where a lot of the tooling in particular and the way that people are describing agents today about hiring labor versus people is actually helpful. But it is a challenge for founders because you still have to understand what your go-to-market motion is and how you scale it with the unit economics of the product and business that you're building.
AP: And what about when they ultimately do hire salespeople? Is the role of the salesperson changing in any way? Such as how they're compensated, the quota per sales rep, or the work structure?
PT: People can do more with less these days. Specifically on the selling side. So if you look at pre-sales versus post-sales, you see this convergence back into account manager role as well. What you're expecting now with AI is that an average account manager can actually take on more customers. And this isn't necessarily a reflection of the economy, it's really a reflection of the new tooling and technology that has emerged. What would've taken you an hour to put an account plan together or do research on a company, you can do in a minute with a pre-tuned GPT prompt.
And so a lot of things are just much, much easier to do. A lot of that efficiency is actually going back to the company where you can have higher quotas, you can have more accounts assigned per account manager, you can do more automated deflection on the support side.
AP: Have you noticed that the greater potential for productivity resulting from using tools like Clarify is changing expectations from investors or board members? It's such a classic conversation in the boardroom to talk about quota achievement on average per rep, or ramp time per rep. Do you think those expectations are already changing and if so, are you able to quantify those? Has the actual quota for a Series A sales rep changed over the last year or two?
PT: A lot of folks, specifically if you think about laggards or late adopters, are still operating with the old numbers of what's possible. And so this provides an arbitrage opportunity for folks who are really, really good at their job at the moment. I think over the next two or three years, what you're going to see is that the cream rises to the top. You're going to see reps that are just crushing quota and then that's going to push the numbers up anyways because that's going to change the underlying baseline of what people are expecting.
But yes, generally speaking, the companies that we have that are using Clarify that are the most productive are doing much more with less, and they're scaling ahead of hiring. Where traditionally, if you think about building pipeline, you might have to hire a couple of marketers, you might have to go spend six months to build the pipeline in order to close it. Or we're seeing that a lot of these companies are actually moving much quicker than that because they have the right tools and they're thinking about the systems the right way.
AP: I can say from experience, it can actually be very helpful to overcompensate your reps in the early days, right? As you said, they crush their quota, they tell all of their friends and then everyone wants to join your company. So yeah, there might actually be an advantage of just keeping expectations the same when using Clarify — help your reps massively overachieve and that'll make hiring your team that much easier.
PT: Yeah. You want your early salespeople to crush it.
AH: We're not yet at the point where machines can do everything. So at the end of the day, whether they're on calls, whether they're creating outbound lists, whether they're running tools, what I'm finding increasingly is there are still jobs to be done. There's still work that has to happen with real humans because AI is not the end all be all for every single thing. I can make agents to do ten times more than I would've been able to do last year or five years ago, but there's still work that actually has to be done by a human using these tools. So we're in this interesting period of time where tools can't talk to one another yet and we can't send agents out to work fully autonomously as humans. So what do you do in the meantime? Where this actually leads is that I'm seeing sales and marketing blend a lot more than I've ever experienced in the past.
Even in our own experience here at Clarify, we have a marketing lead and a sales lead. If you dropped an outsider into a position in the company to observe them, you'd probably ask who's doing sales and who's doing marketing? Because these things are so inherently related, Chris, Patrick, Travis and I are all on sales calls because there's enough capacity for it. But at the same time, both Travis and Chris are working on tools, workflows and Clarify, helping scale our outbound motion. And again, in the past I feel like these would be very bespoke roles that wouldn't overlap a lot across departments.
AP: Great example. I'm wondering if you could talk a little bit about other examples of founding teams that you'd consider to be best-in-class and using Clarify or generally adopting these principles of autonomous go-to market. What can other people learn from what they're doing?
AH: Two come to mind, two customers that I really enjoy working with and I think are amazing. One is Pranav at Paramark. He's actually a long time marketing expert and he works in the attribution space. Won't go too much in the details. Paramark is a cool attribution incrementality testing tool. And it's a really interesting perspective, especially because he's deep inside of HubSpot and Salesforce for his customers to help them understand how to attribute the source of traffic across a lot of marketing channels.
And people don't know this, but one of the veins of every CMO's existence in a B2B business is how do you do good marketing attribution tracking in a tool like a legacy CRM? And most of the time, people just kind of throw up their hands and say, "Hey, data engineer, can you just help me get this into Snowflake so I can figure it out there?"
And so what's interesting about Pranav in particular is he's using Clarify because it's helping him as a founder execute on hundreds of sales conversations, even while he's deep in other people's CRMs. He's helping them figure out attribution. One of the things that's happening with him is we're figuring out our own attribution model and how to make it better than the default expectations inside a traditional CRM. So, he's a great early adopter.
We also have Brendan at Volca. Brendan is creating a company that does offline referrals for the trades. So trades where people can effectively refer folks by business using a platform and a texting app. And what's really fascinating about it is he's pushed us and challenged us a lot to think about mobile and the video of capturing meetings offline. And today, if you have a conversation at a coffee store or if you're in New York and you meet up with somebody and you have a pretty interesting sales combo, where does that context go?
You're kind of screwed. You've lost the data and you've lost the thread around what's happening. And so he's really challenging us to think about how we pull in offline data. Perhaps through a mobile app? How do we use an offline app?
For example, we have our Clarify recorder. This is kind of new, but we have the ability to record offline data and commute that into a summary. So people who are familiar with Granola where it can kind of record in the background with a bot and then create summaries for you. We can do that already inside Clarify because we have a desktop app. And so it reinvents the idea that you can bring context in the CRM regardless of your business type. He's a really cool, interesting early adopter. And then when we were talking about this, me and Pat also talked about what gave us inspiration before we started Clarify.
And even though Ramp was one of the reasons why I wanted to build Clarify, I also would say it was the most advanced go-to-market motion and machinery I'd ever worked with. We had some brilliant people and actually my former boss at the time was Gene Lee, one of the co-founders and he's a classic growth engineer. But I think he found himself in this position of being a revenue leader and a revenue engineer. And we had built a really complex piece of machinery around the existing legacy CRMs. We had built complex attribution, complex enrichment water flows, complex lead data quality routing, pass marketing data all the way through to our attribution vendors and then onto our paid ads category.
So one of the things that he taught me and that I took away from that experience is that go-to-market is becoming an engineering driven department. And that's something that we apply very heavily to ourselves. We not only obviously want to build things that scale for all of our customers, but that's just the philosophy and approach that I think the best go-to-market teams are taking is that it's not a non-technical discipline, it's actually an engineering driven discipline and you have to equip your revenue team with the right engineering tools and people to be successful. Pat, I don't know if you want to talk a little bit about Kevin at Ravenna or anybody else.
PT: I'm happy to. One of our customers is Ravenna, which has taken on the ITSM category trying to build an AI native version of ServiceNow. And the nice thing about Ravenna is they're just spending a ton of time building out agents effectively what we'd call a scaled engineering effort where they're trying to codify a lot of their practices. Whether or not it's things like scaled SEO where they're writing content or whether or not it's their automated outbound approach as well. But they're thinking in the context of an agent first mindset. This is still novel for a lot of organizations out there where they're wondering instead of hiring somebody to do this, how do we actually codify? How do you build an agent or hire an agent to actually work on this? They're definitely a company that I love working with.
And then similar to Austin, just coming from Atlassian and spent a lot of time there thinking about what kind of product led sales looks like. Atlassian moving from your traditional PLG company to a company that now has many, many sellers working in the vast majority of the Fortune 500 now with million dollar plus contracts.
Just thinking about what tools, systems and incentive models you have to put in place for an organization like that to scale to over 5 billion a year in revenue. It's just been a great experience being able to follow folks similar to the ex-CRO Cameron Deitch just learned a lot from watching it from the sidelines, how to scale the enterprise motion and data center business there.
AP: How about other functions that a founder might be involved in at a series A company or potentially managing through an executive? How are they changing as a result of autonomous go-to-market? I'm thinking like sales development, marketing product. You talked a little bit about marketing, but I'd love to hear your general perspective.
PT: Generally, the nice thing about being a founder is you have purview across all the different parts of the organization. You typically have your hand in many of these different functions. And so when you think about the areas that I find that it's most compelling is just the narrative. So, we record all of our customer interactions and calls with Clarify. So we have the entire activity history of every interaction that we've had. We have every single customer call. And then being able to mine that data today to not just understand the customer's biggest pain points, but when we think about building battle cards, how do we look at that data as well?
We have a bunch of information from people looking to switch off of other third-party incumbents to Clarify. And so why are they switching? How do they think about pricing and packaging? What are the features that they're asking us for, right?
This data that we have is really easy for us to mine. When you think about not just business development from the product positioning, marketing, product research, but being able to do better roadmap planning, this is all unlocked based off the way that we've designed and architected Clarify to begin with. And for us, this is the power that we want to be able to give to our customers specifically when it comes to that semantic search or ask AI style functionality. Because it's very, very powerful not just for go-to-market, but for the rest of the broader organization as well. So that's one of the changes that we've seen is that this whole notion of where's this corpus of information exist isn't in your STLC tool or in a spreadsheet anymore, it's really in your CRM.
That's what we're trying to be able to unlock for the rest of the organization. Where today traditionally your CRM is really just used by your go-to-market team. So even a great example at Atlassian. Atlassian's 15,000 people, they have 3,500 Salesforce licenses, which means the vast majority of the company doesn't have access to customer data. Same thing at Amplitude. 800 people, we have 400 Salesforce licenses. So where does that data exist and how does the rest of the organization get access to it? This is something that we're trying to unlock even for our own customers.
AP: It just strikes me that the breadth of features that you have, even just at a more foundational level, the breadth of use cases that Clarify is able to address is so big and I think so much bigger than people normally attribute to CRM, as you said. I mean, gathering customer feedback, that's not something you would normally think of as that data is natively living in your CRM. I'm wondering about the implications of Clarify for the broader tech stack that a series a company might have. What tools are you replacing?
PT: Quite often when we work with a company, they either have an existing CRM that we're ripping out or they're starting from scratch. So it's either a net new CRM implementation for us or it's a rip and replace, something like HubSpot or Salesforce or you name it.
The other things that we're typically replacing are their call recorder. So they might have Fathom, Otter, you name it, but we're specifically trying to consolidate as much of that workflow into CRM as much as we can. The other areas that we typically are starting to move more into are things like your marketing and sales automation stack. So folks might have Apollo, on the upper end of the side. They have something like Outreach. And we're trying to make it so that it's easy for you to effectively do customer engagement at scale, effectively, try to help build pipeline.
And that's another area that we're getting pulled into from our customer base today. Beyond that, a lot of it's just the waterfall enrichment providers. So we do a lot of waterfall enrichment just natively inside the CRM. We do a lot of pipeline building natively inside the CRM for you. And then a lot of it's more around productivity, so things like meeting prep, task management, pipeline management, email follow up. As Austin was alluding to earlier, we effectively have this ambient sales agent that just listens to all the activities that you're doing and helps guide you to the outcomes that you're looking for as a team.
AH: We're obviously our own best customer. And so we're designing our own tech stack around Clarify where it's out of the present while still being pulled up market by people who are trying to use Clarify in a sea of other solutions and tools. So one of the things that we try to do internally and especially happening in the last quarter, in the future quarter coming up is we ask what are the most expensive tools that we have to use on go-to-market to be successful in attaining our revenue goal? And if it's more than a couple hundred dollars, we have serious talks between me, Pat and Andre about what we need to do to go build this inside of Clarify. Again, not because we're trying to compete with everybody, but the reality is, is if we're feeling this pain, all of our other customers are feeling the exact same pain.
So then it becomes a priorities and creation question around what are the biggest rocks? And quite literally, we do this exercise often when we ask people, what's your willingness to pay with different dollar amounts on different features? We have that willingness to pay because we literally are paying for other tools right now that could live inside Clarify. And this is a very different approach than what a lot of people take in go-to-market. The default assumption is that you should integrate a wide variety of tools across a big stack. It gets complicated and hairy and nasty. Our goal is actually to minimize that complexity by building things ourselves.
AP: I'm thinking about another category that you referenced a little bit earlier, note-taking. It sounds like Clarify will handle all of my note-taking and recording needs, so I don't need Granola anymore.
AH: That's correct. Technically, we could have Clarify running right now. You wouldn't even know about it. There are two versions of the note-taking app that we've built. One is obviously what everybody's used to. You have a custom call recorder, it joins your Zoom or Google meeting. You can brand it, you can put a logo on it, and that's really great when you have a transparent forum or if you're recording internal meeting or something like that.
But there's lots of times where you want to take notes and you're not trying to necessarily record the voice of the person, but you want to have all the details about that conversation recorded. And that's obviously why Granola was invented and what they're good at. We've built that natively inside the Clarify app. In the top right corner, you can actually click a little button and start the meeting recording. It's called "local recording right now."
It records and transcribes everything for you. And then compared to traditional call recording software, we actually will do a couple things. We will scrape that for deal info. We'll update the deal. We'll create the deal if it doesn't exist. We'll give you a meeting summary. We'll prompt and remind you about the next steps. We'll create tasks for you.
All the things that normally a sales rep would do after a call, usually at the end of the day when they're tired and exhausted, Clarify is doing in the background for you automatically and very quickly. It's guiding you throughout the day. It's guiding you throughout the sales process. And this call recorder can do it both natively on the desktop in the web. You don't have to have a bot join your calls anymore if you don't want.
AP: So a lot of people have been raising this question of will the GenAI wave benefit incumbents or will it benefit startups? And obviously there's probably a different answer to this question in any given category. I'm just curious to know in your category of CRM, why do you think GenAI will benefit new companies like yours as opposed to HubSpot and Salesforce?
PT: In any major technology wave, the vast majority of the benefit goes to new entrants in the market. Think about when we went from mobile to desktop or web to mobile or from server to cloud. These were massive shifts that occurred that let Salesforce take on Siebel—a great example there. The similar comparison can be made with AI, which is that most of these legacy incumbent vendors ended up building themselves into a box where it's really hard to then be able to adapt with the new technology that exists today. A great example of this is just the underlying primitives for AI to fully exist. You need both structured, unstructured and then time series or activity event data.
And so we've built an architecture in Clarify with that in mind from the beginning, so that our AI can take advantage of all three of those types of data. And that's not something that's easy to go just add on to an existing vendor. And this is where you see Salesforce trying to acquire Informatica for a billion dollars this week. So, there's massive shifts that happen in market and then most of the incumbents will end up trying to acquire their way into being able to compete. And that might work for some folks, but generally when you think about building the right product the right way from the start, you end up with a better customer experience from the beginning.
AP: I know that you all have made some important decisions about your architecture and you've invested just a lot of thinking into how to make it right for the AI area. Can you talk a little bit about some of those big decisions that you've made?
PT: Everything is multi tenant / single tenants so every customer has an isolated warehouse of all their customer data. Everything in our application interfaces via SQL, so there's no reason that we couldn't run your data on-prem or in Snowflake or Databricks in the future. These are things that kind of allow us to be able to provide not only a better application experience for customers, but be able to meet the customer where they are, allow them to be able to directly write SQL queries against the data that they have as well.
The reason that this is valuable is that when you look at a company like Salesforce, they're trying to get all of your data into Data Cloud. They want you to centralize all that data there. Whereas generally speaking, we're in a kind of postmodern data stack environment where people want to be able to own their data. They want to be able to centralize it, manage it via their own ETL processes, and build views on top of that data. And we're much more philosophically aligned there with the modern data stack than previous generations of companies.
AP: Thinking about other trends precipitated by GenAI, do you think that the GenAI wave favors best of breed products or will it create a new era of consolidation across products?
PT: We're just going through a re-bundling phase at the moment. So I'm bundling, un-bundling every decade. We're definitely in a bundling phase right now, where if you look at the average number of tools in go-to-market and the enterprise is 23 tools. This is Salesforce's own data. And effectively that causes a lot of frustration because you have your pre-sales team in one tool like Outreach, you have your sales team in something like Salesforce, even though they don't want to be in it. And then you have your post-sales team and something like Gainsight, which you're obviously very familiar with. And that means that you have no system of record, you have no source of truth. All of the workflow's not in one place to be able to manage.
This is causing just a lot of frustration today, right? And then these tech stacks or these go-to-market stacks become super convoluted. This is effectively what we call the "Frankenstack." And then they're expensive over time. We believe that there's an opportunity and we see our customers asking us to build more and more capabilities into the core platform that we offer because they don't want to have to go buy yet another solution on top of it.
AP: That definitely makes sense. I notice a lot of very specialized AI agentic tools cropping up that are catering to some kind of go-to-market need. There's a bunch that are focused on the cold emailing space. There's a bunch that are focused on potential churn risk, expansion, opportunities, creating workflows internally around all of those things. Do you think that these tools should exist or do you think that ultimately Clarify or some other theoretical competitor will consolidate all of these spaces?
PT: Consolidation is inevitable in certain categories, but it's worth including go-to-market tooling. And so even if you look at Salesforce, it started in a very different space than they're today. Now they have a suite of products. HubSpot, started with a point solution, now they have a suite of offerings. So consolidation is inevitable.
The question with any of these point solutions is what's the durability or defensibility of what they're offering compared to that being offered by one of the larger incumbents or platform teams? This is why we started very pointedly building a platform company from the beginning because we wanted to make sure that we weren't just building a nice to have, but we're also building a durable business from the start.
And we thought about it pretty clearly in the amount of investment that we made into platform at the beginning. The vast majority of the way that we think about it is we will have to integrate with a lot of these solutions. We're an extensible platform. We'll integrate. We'll also offer for capabilities as it makes sense to our customers. And this was the same challenge that every platform team, including HubSpot and Atlassian and Salesforce run into, which is what do they feel like they need to own and what do they feel like they need to integrate with as far as best of breed?
AH: Yeah. And for what it's worth, there are going to be a lot of businesses that either don't have a CRM and Granola is an amazing solution for them. But for people who have a CRM or want a CRM and are trying to integrate another call recording with their CRM, Clarify is a better solution. I mean, we've literally had this conversation with the people where they're saying, "I'm paying $2000, $3000, $4,000 a month just for call recording to get that data into HubSpot."
What if that was just part of the CRM? And obviously we want the context because that's how we're able to derive these AI solutions for you is by having that context. The whole wave of the future is based on unstructured data. So, if you have unstructured data and you can parse that and apply it to the CRM, then you're able to actually provide a lot of value. For us, it's almost like a loss-leader. We don't care how much the call recorder costs, because we want you to use the tool. But for other people, that is the core business and I think that's a primary difference between us and standard call recorders.
AP: I want to talk about the implications of your product for your customers and what kind of customers specifically would benefit from using your product. How would you describe your ideal customer profile? What types of companies do you focus on?
PT: We're mostly working with B2B SaaS companies today. Most of them are early stage businesses, many post-revenue, post-product market fit. This is quite often the first CRM that they brought through the door and they're looking to scale out their go-to market motion. A lot of the challenges that folks typically have when it comes to building out a revenue operations team or having to hire and grow on the post-sale side, we're trying to solve just right out the gate. Not only does Clarify work for pre-sales and the active sales side, we also dip our toes in the post-sales side. So that you can understand things like customer adoption and customer health directly within your CRM.
AP: And when is the customer ready for Clarify? Are there certain tools that I already need to have in place or a certain stage in my go-to-market that I need to have reached?
PT: We've had dozens of people size companies join us. We've had people as early as one or two people just with an idea trying to get started mostly on the customer discovery side. It really just depends on what you're looking to achieve. I think a CRM is helpful for tracking specifically deals, even at the early stages of company building of who you're talking to, what does customer discovery look like, what are you learning, what are the lessons learned? And then helping with the follow maybe when you have a product to market that you can actually bring to market. But I'd say there's no company too small that Clarify wouldn't be helpful with today.
AP: And which specific people at the company should be using Clarify?
PT: We work primarily with founders. A lot of the times when we're engaging with folks at the earliest stages of company buildings, we're talking directly with the founders. The founders are the ones that are signing up for Clarify. That's primarily because they're looking for a system to be able to manage the chaos of early stage company building, which, as you know, is super hard and generally a spreadsheet. That can only get you so far.
Clarify automates a lot of that process for you. Generally, once we go from founders to having a head of sales or your first couple of sales and marketing hires, that's generally where I feel like Clarify tends to thrive as well, because there's just more chaos to manage.
AP: What kind of effort does it take to set it up?
PT: It's super easy. You can get up and running in five minutes.
AP: Literally five minutes?
PT: Five minutes.
AP: Wow. Okay. And I guess that five minutes is spent what? Signing into my Gmail. What else?
AH: Telling me how you heard about us so that I have good attribution tracking. And then usually 30 seconds for your inbox to sync or however long it takes.
AP: So it sounds like I don't need a RevOps person to set this up or administer Clarify.
PT: No. If anything, we're trying to build more agents into Clarify to help give you the proactive coaching that you need.
AP: So you're not going to have the future of Dreamforce with a bunch of Clarify administrators all converging on San Francisco. Might be a different profile someday. Not the administrator, but the autonomous sellers maybe.
PT: Yeah, exactly. I mean, community building is definitely something that we think a lot about, but more in the context of the seller, the person carrying the bag.
AH: Yeah. And a lot of sellers often want to move into RevOps and so a good resource for people if they don't know is we built a whole RevTech Academy and RevTech course that we have online in Clarify.
If people want to teach themselves how to be a Rev Operator before they take the jump into Clarify, it's on our website. It's a five-part series, couple dozen hours of videos that me, Chris, and some other folks created from the industry.
AP: Wrapping up here, what final piece of advice would you have for founders who are trying to navigate the GenAI world for go-to-market?
PT: The very simple advice that I have is just don't get locked into the old way of thinking. We're reimagining everything at this point within technology—how you build products, how you service customers, and how you sell. So, make sure that you're not locked into legacy systems that are holding you back.
AP: And at a minimum, talk to Patrick and Austin because they can probably save you a lot of work in doing that homework yourself. They can help you get up to speed. Thank you guys so much for joining us today.
AH: My pleasure.
PT: Thanks, Allison.
AH: Thanks for having us.
