The company teaching software to find your next customer - so you don't have to.
Somewhere in a B2B office, a marketer opens a laptop and watches a campaign assemble itself. Prospects get found. Lists get cleaned. Messages get written, scored, and sent across channels. A week of grunt work happens in the time it takes to refill a coffee. The human in the chair did not lift a spreadsheet. That is Landbase on a Tuesday.
Landbase is an agentic AI company building autonomous go-to-market technology - the unglamorous engine room of sales and marketing, automated. Its product is a set of AI agents that prospect, enrich, write, send, and learn. The company is small (around 51 people), young (founded 2023), and well-funded (about $42.5M). It is also, by its own framing, allergic to busywork.
Software should work for you, not the other way around.- Landbase company mission
Here is the uncomfortable truth the industry has politely ignored for two decades: most go-to-market work is repetitive, and most of it is done by hand. Reps build lists. They guess at who to email. They copy, paste, personalize, and pray. Tools multiplied - a database here, an enrichment service there, a sequencer, a scorer, an analytics dashboard - and somehow the job got harder, not easier.
The result is a stack of point solutions held together by tabs and willpower. Conversion rates stayed low. Campaigns took two weeks to launch. And the people hired to build relationships spent their days feeding software instead.
They're not just solving outbound - they're building the foundational platform for how modern companies grow.- Guy Oseary, Sound Ventures
Landbase's bet is that this entire workflow - the finding, the writing, the sending, the optimizing - is not a human job at all. It is a model's job. One that can learn from every campaign it runs.
Daniel Saks had built a unicorn before. As co-founder and co-CEO of AppDirect, he spent years inside the machinery of enterprise software distribution - and inside the daily friction of selling it. A Forbes 30 Under 30 alum, he started Landbase in 2023 on a simple premise: the GTM motion was ready to be handed to agents.
He did not do it alone. Emily Zhang - founding product leader at the unicorn OysterHR, with stops at Carta and a Harvard MBA - joined as co-founder and Chief Product Officer. Hua Gao, a Stanford PhD who co-founded EverString (acquired by ZoomInfo) and directed machine learning there, came on as co-founder and Chief Data Scientist. The team since added a CTO who scaled engineering at BigCommerce and a growth chief out of EverString.
The founding team had already lived the GTM data problem - at EverString, ZoomInfo, and AppDirect - before they decided to automate it.- From public company materials
It is a slightly ironic origin story: a group of people who spent careers building the very sales-data tools they now intend to make obsolete. They would presumably call that progress.
Daniel Saks, Emily Zhang, and Hua Gao set out to automate the go-to-market motion end to end.
Round led by Kevin Hartz's A*, with 8VC, Firstminute Capital, Inovia, Picus, and General Catalyst.
A domain-specific "action model" for go-to-market - AI that takes steps and learns from outcomes.
CIBC Innovation Banking extends debt financing to fund expansion.
Recognized by Gartner; platform opened to a free preview tier.
Co-led by Ashton Kutcher and Guy Oseary's Sound Ventures with Picus Capital; existing backers return.
Most AI in sales writes text. Landbase's model takes actions. GTM-1 Omni is built as a domain-specific "action model" - it decides who to target, what to say, and which channel to use, then watches what converts and adjusts. The approach borrows from reinforcement learning, the same family of techniques behind game-playing AI, pointed at the decidedly less glamorous task of booking meetings.
The newer GTM-2 Omni extends this into a multi-agent system: several specialized agents coordinating across the workflow, trained on more than 40 million B2B campaigns and 50 million analyzed sales conversations. Underneath sits a database of 300M+ contacts and 24M+ accounts, with enrichment, intent signals, and lead scoring built in.
Domain-specific action model that runs campaigns and improves from performance feedback.
Coordinated AI agents trained on 40M+ campaigns to run the full GTM motion autonomously.
Cut campaign launch time from roughly 14 days to minutes via agentic search and orchestration.
300M+ contacts, 24M+ accounts, with enrichment, intent data, and AI lead scoring.
From fourteen days to a few minutes. The campaign did not get smaller - the waiting did.- On Landbase's Campaign Feed launch
Skepticism is the correct default for any company promising "x times better." So here is the claim, stated plainly: Landbase reports a 4-7x conversion uplift over manually built campaigns. The chart below frames the floor of that range against a manual baseline. Treat it as the company's claim, not a law of physics - but it is the number the business is built on.
The traction line is steeper. The company reports 825% revenue growth since the start of 2025 and around 150 paid customers within roughly a year of launch. Gartner named it a Cool Vendor in 2025. Investors noticed: $12.5M at seed grew into a $30M Series A co-led by Sound Ventures.
Acquired within about a year of launch.
Reported since the start of 2025.
Analyzed to learn what converts.
The pitch is not "replace the salesperson." It is "stop making the salesperson do the robot's job." Landbase frames a future where sellers stay focused on relationships, marketers stay focused on creative, and the administrative scaffolding of growth runs itself. The machines get the spreadsheets. The people get their afternoons back.
That framing matters in a market nervous about AI taking work away. Landbase's answer is that it is taking away the work nobody wanted - the list-building, the data-cleaning, the fourth follow-up - and leaving the parts that need a person.
Sellers stay human. Marketers stay creative. The busywork goes to the machines.- Landbase's stated vision, paraphrased
Return to the marketer watching a campaign build itself. A few years ago that scene was a fantasy - the work was real, manual, and slow. Landbase's argument is that it is now ordinary, and getting more so with every campaign the model runs. Each one becomes training data for the next.
The skeptic's question remains fair: does the uplift hold at scale, across industries, against an arms race of competitors building the same agents? Apollo, ZoomInfo, Clay, Outreach and a wave of AI-SDR startups are all chasing this. Landbase's edge is the loop - a model that learns from its own outcomes - and a founding team that has shipped at scale before.
The coffee is still warm. The campaign is already out the door. Whether that becomes the default way companies grow is the open question - but Landbase has put $42.5M and a domain-specific model behind the bet that it will.
The work didn't disappear. It just stopped needing you to do it.- The Landbase thesis, in one line