00:00:00 · Gil Feig, Molly O'Shea, Shensi Ding
[00:00:00] S0: We power critical functions for a lot of businesses. Their core could be powered and heavily driven by merge. So these sort of things, we cannot break. We cannot go down. Everything's four, five, six, nines of uptime. And if you lose that, you can lose all your customers overnight. [00:00:13] S1: Some of your customers are names like OpenAI, Netflix, Uber, Mistral, Dropbox, Freshworks, and more. [00:00:19] S2: So we do search some of the largest AI companies in the world powering their AI search functionality and also connectivity in their products. Consumer expectations are higher now. Like, you just expect significantly more automation, and so if the SaaS platform cannot keep up with the expected automation. It's just hard to compete. [00:00:32] S1: What is the state of cybersecurity in this layer of AI? [00:00:36] S0: They now speak English perfectly. They now write code perfectly, and they now have unlimited manpower all driven by AI. The second you connect it to tools, which is what everyone is trying to do right now, that's where everything goes wrong. It's so hard to block them because they're coming from IPs all around the world, and all it takes is one, and they could mean the end of your company. [00:01:04] S1: Alright, Shenzi, Gil, welcome to Sorcery. Thanks for having us. [00:01:08] S0: Thanks so much. [00:01:09] S1: This is a Merge special. We have a CTO and a CEO on. [00:01:13] S0: We're happy to be here. [00:01:14] S1: So what's going on? Don't think we [00:01:16] S2: don't get canceled. I don't
00:01:16 · Shensi Ding, Molly O'Shea
[00:01:16] S2: don't get canceled. I don't [00:01:17] S1: think you're gonna get although we did have some spicy pre podcast talk. [00:01:22] S2: Yeah. We won't talk about Staples High School gossip. [00:01:27] S1: No. So you guys are on a tear. You have a lot of big announcements that keep on rolling out. What's the latest? What's going on? [00:01:33] S2: Yeah. Honestly, it's been really exciting for us. Around like a year and a half ago, we made a pretty concerted effort to do like three efforts in order to really move ourselves into the AI space. One of them was using AI really aggressively internally, pivoting our existing product to sell or not pivoting, but like adjusting our current comp product to sell to AI companies, and then also launching our own AI products. And those bets have really paid off, especially in the past year and a half. So it's been really exciting seeing like all the hard work that we put in, finally coming to fruition. [00:02:01] S1: So what are those products today?
00:02:01 · Molly O'Shea, Gil Feig
[00:02:01] S1: So what are those products today? [00:02:03] S0: Yeah, so we have now a suite of three products. We have Merge Unified, which is our original product. It helps companies sync data. So basically, want to bring that in, power something like enterprise search, do Rag. You take that, you ingest all the data, we normalize it, and it's there for your customers. It helps build a really good search experience. Since then, we've also launched Merge Agent Handler, which is essentially one, sort of MCP server you can connect to to help your customers offer or to offer hundreds of integrations to your customers inside of agents. And this can be used for internal agents within a company when you're building your own. It can be used for external agents. So if you're building a customer support bot, for example. And then it also can be used to power just internal use cases. Your whole team is using Cloud Code. Your team is using, you know, Cloud or ChatGPT or whatever it is. The the connectors all just appear in there and work with whatever AI tools you're using. And then lastly, we launched Merge Gateway. And Merge Gateway is infrastructure that just makes it really easy for you to switch between hundreds of different AI models, and route them based on a ton a ton of different policies. It has security layer built in, and it has a lot of smart routing policies, cost saving policies, and dashboards that make it easy for your whole company to really optimize your AI spend and usage.
00:03:20 · Molly O'Shea, Shensi Ding
[00:03:20] S1: One of the observations that I've had over the last two, three years was, you can see when companies don't really make a concerted effort to pivot or rebuild or embrace AI. And you can tell either about what they're posting about online, who they're engaging with, like how their products are developing, but you guys did make that concerted effort. What was that process for you internally, especially with with your customers too? [00:03:50] S2: I mean, it was really hard. There were a lot there was specifically one really, really big deal that we wanted to close, and it was going to take up like 90% of our resources. And it was really hard to figure out, like, okay, how do we end up, like, taking how do we end up finding resources to start building for the future instead of just building for right now? And thankfully, even though it was honestly at the time really hard, the deal paused for a month. And during that time, we actually got a lot done. We we, like, finalized the idea that for our, like, second product, which was the merge agent handler, we also started really aggressively leading into AI coding. So Gil and I, like, paused back on the keyboard, like, using Cloud Code really aggressively, using Windsurf really aggressively so we could also learn how to code, with AI. And that month actually really transformed the business. Because with us having firsthand knowledge of how powerful AI is from zero to one, it allowed us to see what was possible with our existing products as well.
00:03:50 · Shensi Ding, Molly O'Shea
[00:03:50] S2: I mean, it was really hard. There were a lot there was specifically one really, really big deal that we wanted to close, and it was going to take up like 90% of our resources. And it was really hard to figure out, like, okay, how do we end up, like, taking how do we end up finding resources to start building for the future instead of just building for right now? And thankfully, even though it was honestly at the time really hard, the deal paused for a month. And during that time, we actually got a lot done. We we, like, finalized the idea that for our, like, second product, which was the merge agent handler, we also started really aggressively leading into AI coding. So Gil and I, like, paused back on the keyboard, like, using Cloud Code really aggressively, using Windsurf really aggressively so we could also learn how to code, with AI. And that month actually really transformed the business. Because with us having firsthand knowledge of how powerful AI is from zero to one, it allowed us to see what was possible with our existing products as well. [00:04:42] S1: Did you also notice when you're doing that the vulnerability of your business before?
00:04:42 · Molly O'Shea, Gil Feig
[00:04:42] S1: Did you also notice when you're doing that the vulnerability of your business before? [00:04:47] S0: I mean, I think absolutely. I think we realized in that moment, it was the classic innovator's dilemma where we had, you know, this product, it was growing really fast, it continues to grow really fast. But we also knew where the space was going, and we wanted to put as many resources as possible in our newer products. And so during that month, since he was talking about, we also realized, like, we do not have this ability to just put unlimited resources on this new thing. How can we get more with less? And that was why we we knew we had to invest in AI. We knew we had to be able to build new products and and, you know, adapt our existing products with just a couple of people. So honestly, actually building our our next product agent handler, we had one engineer and me and Shenzi, and we were helping on nights, weekends, we did whatever we could half because we needed to contribute, we needed to help. And the other half was if we are the leaders of this company, we have to know everything there is to know about how AI works, how you build with AI so that one, we are more effective, and two, we're building for where the puck is going.