The Flockler co-founder's new venture, Landing Rabbit, has its first paying customers. The harder test is whether it can win buyers who never helped build it.
For more than a decade, Toni Hopponen built Flockler, a social media aggregation platform whose customers included Metallica and Harvard. After selling that business, the London-based founder is back at the very beginning with Landing Rabbit, an AI-powered tool that generates landing pages in a company's own brand style. Its first paying customers have arrived, and with them a new question about how the product will sell to strangers.
Flockler began as a conventional, sales-led company selling to larger organisations. Its product gathered social media content and displayed it on live TV broadcasts or branded websites. Over time it became fully self-serve, with customers arriving through Google Ads, SEO and word of mouth rather than a sales team. Its early blog content produced few leads for the first few years, but the company eventually learned how to convert visitors from search and paid campaigns. Even Metallica signed up without speaking to anyone. Hopponen first assumed the band's appearance on a trial dashboard was a data error, and only spoke to its team after it had upgraded.
The sale itself was a long negotiation that stayed uncertain until the deal was signed. Hopponen found it hard not to tell his whole team, some of whom had been with the company for around ten years, while still planning the months ahead with them. All existing employees stayed on after the deal. The first day afterwards was tough, he said, and it took around six months to realise he wanted to start again. Selling forced him to cut ties with the reasons founders build to justify working so hard, such as clients, employees and investors. What remained, in his words, was that "I just love the building part."
Landing Rabbit grew out of a frustration from his Flockler years. Google Ads campaigns perform better when the landing page matches the keyword, yet he always had more campaigns with weak pages than strong ones. He assumed this was his own shortcoming as a self-taught marketer from a tech background. Then he interviewed others after leaving Flockler and helped another company with its marketing, and he saw the same problem everywhere. Pages took weeks because one person plans the content, another designs it and another builds it.
She concluded that systems resembling human brains would need supervision, an idea she connects to Marvin Minsky's The Emotion Machine, which closes by arguing that neural networks will need external critics. The large enterprises she spoke to had no plans to build that capability themselves.
The platform centres on an AI agent manager, a category Gartner refers to as a guardian agent. Businesses connect agents from platforms including Agentforce, OpenAI, Anthropic and Intercom, then give the manager each agent's role, goals and guidelines. It reviews agent activity in real time, sends alerts when an agent goes off course, grades outputs to speed up human review, and pauses multi-agent workflows so a faulty step can be redone. In a customer service case study the company is preparing to publish, Mamut says guideline violations fell from 5.9 percent to under 1 percent and knowledge gaps dropped from 8.5 percent to under 6 percent. Her argument is that even the best agents carry error rates of 1 to 3 percent, and that a second agent checking the first is how enterprises reach the reliability they expect from software.
The harder question is durability. Mamut believes the SaaS-era approach of finding a workflow friction and building a product around it now has limits, because software is easy to copy and large AI labs may absorb today's problems. Wayfound holds a patent, but she is candid that others are trying to build what it has built, and that some will get there. Her focus is instead on assets she believes customers will not want to give up: a partner ecosystem, including a partnership with Salesforce's Agentforce, and trust. The company's tagline is "trust in intelligence," and it secured SOC 2 Type 2 compliance before taking on its first customer.
Mamut, whose team works from hubs in San Francisco and Raleigh, North Carolina, describes the longer goal as helping companies move toward what she calls a multi-sapiens workplace, where people and AI agents work alongside one another. Within three years, she expects Wayfound to be the critical layer for that interaction. As she sees it, the need is inevitable; the only open question is when enterprises are ready for it.