We created Landbase to use AI to automate business-to-business go-to-market. We have the funds to grow our platform thanks to our Series A ($30M) funding round, which is co-led by Sound Ventures and Picus Capital. In this article, we describe the multi-agent architecture and reinforcement learning methodology of our proprietary agentic AI model, GTM-1 Omni, as well as the outcomes it is producing (4–7x higher conversions, campaigns created in minutes). We'll also talk about the platform's future implications of this funding.
GTM Using AI: From Stealth to Series A
B2B enterprises' go-to-market is ready for change. Sales and marketing teams now manage a dozen systems for CRM, outreach, and prospecting, and they frequently spend as much time figuring out software as they do interacting with leads. Given our founders' background in the GTM industry, we recognized a chance to combine and automate these processes using an AI-powered "system of action."
With the goal of creating the first agentic AI platform especially made for go-to-market execution, Landbase came out of stealth in late 2024. We developed an AI that can locate prospects and start outreach on its own, rather than merely creating another metrics dashboard. Our team, which consists of GTM veterans and machine learning PhDs (formerly from Everstring and NASA/Stanford), worked on this idea for years. In 2024, we raised $12.5 million in a seed round to develop the fundamental technology. As we grew (acquiring 150 customers and increasing revenue by 825% in a few quarters), investors began to pay attention once more.
This June, we raised a $30M Series A co-led by Ashton Kutcher’s Sound Ventures and Picus Capital. For us, this funding is fuel to accelerate R&D and scale our platform to meet growing demand. But what exactly is under the hood of Landbase’s AI platform? Let’s dive into GTM-1 Omni.
GTM-1 Omni: Reinforcement Learning and Multi-Agent AI Inside
Landbase's platform is powered by our proprietary AI engine, GTM-1 Omni. With a suite of action models that can carry out operations in the GTM workflow, GTM-1 Omni is essentially a domain-specific large language model (LLM) tailored for sales and marketing material. To put it another way, it's a coordinated system of AI agents planning and carrying out campaigns rather than a single model. A prospect list may be created by one agent based on an analysis of ideal customer profiles; another may provide customized email content; still another may manage scheduling and message delivery; and so on. In a manner not possible with conventional technologies, Landbase's multi-agent architecture enables it to automate the entire outbound campaigning process.
A vast dataset of B2B go-to-market contacts, including more than 40 million past campaigns and 175 million sales talks, was used to train GTM-1 Omni. This provided our models with a deep understanding of how various targeting, messaging, and sequences function in practical situations. However, we went beyond pre-training. Using reinforcement learning to continuously improve outcomes has been a significant innovation. In particular, we use a technique we refer to as reinforcement learning with human and performance feedback, which combines expert remarks with real-time campaign results as learning cues. The system may, for instance, A/B test two email strategies; if one results in a greater reply rate, the model will give that technique more weight going forward. Over time, GTM-1 Omni becomes smarter with each campaign, optimizing for the metrics that matter (opens, conversions, pipeline generated).
Outsized gains have resulted from this strategy:
- 4–7 times greater conversion rates than manual outbound efforts (we've seen a ~7x improvement even when compared to baseline GPT-powered scripts).
- Sales teams have reduced the amount of time they spend on each lead by 70% as a result of automating outreach and prospect research chores.
- Launch dates for campaigns were shortened from weeks to minutes. (Before Landbase, planning a multi-touch campaign may need 14–30 days of preparation; with our platform, a representative can start a customized campaign the same day.)
In short, GTM-1 Omni functions as a 24/7 high-output AI sales development staff. And it continues to improve. To further bridge the gap between human intuition and machine efficiency, we launched a Campaign Feed interface in April 2025 that allows consumers to observe and comment on the AI agents' actions in real-time.
Upcoming Actions: Expanding and Opening Up
We are concentrating on developing and expanding this technology with the new funds. On the machine learning front, we're developing our reinforcement learning algorithms with more detailed performance data and investing in bigger, more specialized models for GTM-1 Omni. Additionally, we are developing more autonomous agent capabilities. Imagine future GTM-1 Omni agents that can automatically respond to incoming prospect answers or modify your campaign approach as needed.
Making Landbase available to more companies and developers is another top focus. We just released a free preview application so that anyone may test out Landbase's AI. You can register on our website, provide a brief description of your target client, and allow GTM-1 Omni to create a campaign plan for you if you're interested in learning more about how an AI-driven campaign operates. It's a practical approach to demonstrating the capabilities of an agentic GTM platform.
Similar to CI/CD pipelines for software teams, we see Landbase as a key tool for go-to-market teams in the long run. Intelligent agents may take over the tedious, repetitive tasks of outreach and prospecting, freeing up human teams to concentrate on strategy, innovation, and relationship-building. We want to change GTM from a world where people serve software to one where software works for people, as one of our investors stated.
I appreciate you reading! As we develop, we'll keep exchanging technical insights. Please leave a remark below if you have any questions concerning the operation of GTM-1 Omni or suggestions for future features. If you're interested in this field, we're hiring full-stack developers and AI engineers to help shape the go-to-market of the future. Come work with us!
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