Enso raises $15M to build ‘agentic growth hacking’ category and “Redefine Agentic GTM”

enso, a Tel Aviv-based startup that describes itself as an agentic growth hacking lab, has raised a $15 million Series A led by MoreTech Ventures, with participation from existing investor NFX, Phenomen VC, and angel investor Gil Hirsch. The round brings the company’s total funding to $23 million.

The company’s pitch is a departure from the wave of “AI GTM” and AI content tools that have crowded B2B marketing for the past two years. Rather than selling software that helps a marketing team produce more, enso deploys its own engineers and marketers into a customer, builds a system of AI agents around how that business sells, and points those agents at a research problem: figuring out how each distribution platform, from LinkedIn to Reddit to the AI answer engines, decides what gets seen, and using what they learn to open channels the customer’s competitors aren’t in.

Customers include Papaya Global, MyHeritage, Papaya Gaming, Natural Intelligence, Winn AI, along with startups such as Dynamo and Wiliot.

A market where the old playbooks stopped working

enso’s founding thesis rests on a diagnosis that will be familiar to anyone running B2B marketing in 2026. Growth hacking, the discipline that built the consumer internet a decade ago, stopped working when platforms began changing their ranking rules faster than human teams could find new openings. Inbound marketing assumed a person would read the content and a search engine would send them to it; increasingly, buyers ask an AI assistant instead, and the assistant decides which companies to mention. Paid acquisition, the fallback, has become expensive: cross-industry cost per click rose nearly 13% in the latest WordStream benchmark, and Seer Interactive’s tracking found organic click-through on searches showing an AI Overview fell about 61% between January 2025 and February 2026.

“Marketing teams can spend months building a strategy around channels that change before they see results,” Mickey Haslavsky, enso’s founder and CEO, said in a statement. “AI agents make it possible to monitor multiple platforms continuously and act on opportunities that teams would otherwise miss. The challenge is knowing where to focus and how to turn that activity into growth for each business.”

The company’s framing is that every platform is a growth channel on a timer. Each ranking, trust, and recommendation system rewards certain behaviors, and those rules change as the platform evolves. The advantage, in enso’s view, belongs to whoever learns the current rules first, on every platform at once, and that is a research problem rather than a marketing one. The agents, Haslavsky argues, are the researchers.

A complete marketing and go-to-market suite

enso does not sell a self-serve tool. Its model has two parts.

The first is a custom go-to-market system. A forward-deployed engineer and a forward-deployed marketer embed inside the customer, learn how the business sells and to whom, connect to the systems it already runs, and build agents that operate across five surfaces: search and AI-answer visibility; sales outreach across email, LinkedIn, SMS, and voice, timed to a prospect’s behavior rather than a calendar; the forums and communities where buyers ask for recommendations; newsletters and owned content; and social media, where the company says attention is decided in minutes. The marketer supervises the system, approves every playbook before it goes live and every action that cannot be undone, and reports results weekly against a baseline recorded at the start of the engagement, in pipeline terms.

The second is the research function. enso’s agents continuously study how platforms rank, recommend, and cite, form hypotheses about what each one currently rewards, test them at small scale against a control, and turn what works into a channel the customer can run. Each finding carries an expiry date and is re-tested as platforms change. What is learned with one customer is reused for the next, and the results, including experiments that failed, are published on the company’s research page.

That last point is unusual in a category where vendors typically guard their tactics. enso’s published studies include a LinkedIn distribution agent that produced a 143x median reach lift across 24 posts by acting inside the platform’s first-hour ranking window; a Reddit agent that earned 270 karma across 11 subreddits in a week with no promotional comments and generated 28 inbound sales calls; and a Wikipedia citation pilot across nine client domains in which 14 of 62 citations survived to day 30 and began appearing in answers from large language models. The company also maintains an open-source library of AI agent skills covering 14 growth disciplines, which reached 760 GitHub stars in its first four days.

“Agentic Growth Hacking”

Haslavsky coined the term agentic growth hacking and is writing a book of the same name. He previously co-founded RapidAPI, the API marketplace acquired by Nokia in 2024, is a Forbes 30 Under 30 alumnus, and hosts The Autonomous Business Podcast. enso was founded in 2024 as an AI agent marketplace and pivoted to its current model as a growth lab; the company’s leadership includes CTO Omry Hay.

Investors are buying the category argument as much as the product. “Marketing channels are changing faster than teams can adapt, and the newest ones have no playbook,” said Zack Keinan, co-founder and general partner at MoreTech Ventures. “enso treats that as a research problem, studies how platforms decide what gets seen, and deploys engineers and marketers to turn the findings into growth for each customer. We believe it is defining a category, and we’re proud to lead this round.”

About enso

enso’s model is services-heavy by design, which raises the question every investor in the category asks: whether an engagement built around embedded engineers and marketers can scale like software. The company’s answer is the research loop, in which playbooks proven with one customer become reusable for the next, and the open-source skill library, which lets the method travel where the service does not. Whether that produces software-like margins is something the Series A will test.

The second question is the platforms themselves. Everything enso finds is, by definition, a behavior a platform did not intend to reward, and every platform has the power to reclassify a tactic as abuse. enso’s response is its publishing model: disclose, expire, move on. Whether the platforms see it that way remains to be seen.

For now, the company is positioned in a gap that is widening. Paid is more expensive, inbound reaches fewer readers, and the AI answer engines that increasingly sit between buyers and vendors have no established playbook. enso’s bet is that the playbook is discoverable, that agents can discover it faster than people, and that customers will pay for someone to be accountable for the result.