Raffle AI

Suzanne Luritsen had already experienced the startup grind. She'd sold a previous company in 2017 that she'd bootstrapped to about $3 million in revenue. But this time, she wanted to move faster. In July 2018, she joined forces with a professor from DTU (Technical University of Denmark) to found Raffle AI, a company focused on intelligent search tools for customer service automation. The vision was clear: leverage newly scalable AI to provide instant, correct answers to customers and employees while gathering invaluable insights on consumer needs and satisfaction.

What's remarkable is that Suzanne and her co-founder came fully prepared. Having spent a year after her previous exit planning, preparing the business plan, identifying investors, and assembling the team, they hit the ground running. Just three weeks after founding, they closed their first angel round of $200,000. "We didn't have any clients, we didn't have any product basically—we didn't have anything," Suzanne recalls. "But we had the idea and we had the right team." The team grew quickly, with 18 engineers focused on building the AI-powered platform. By early 2019, they'd raised a second angel round of approximately $400,000, followed by a Series A of $2.9 million in early 2020.

Their first customers came from proximity and proximity alone. Raffle operated out of Pure47, an incubation space in Copenhagen shared with larger corporate entities. "We started out piloting with two customers who were sitting in the same space as we were," Suzanne explains. These pilot customers converted to paid accounts, though they eventually churned as Raffle pivoted its product offerings. The company launched its first product in summer 2019 and the second product, Autopilot, in February 2020. Autopilot was the real breakthrough—it handled first and zero-line support for customer service teams, providing AI-suggested answers directly in chat widgets to reduce support tickets.

By the time of this interview, Raffle had 7 enterprise customers, each paying approximately $35,000 annually—putting them at roughly $245,000 in annual run rate. Suzanne herself had been the primary closer, though the company had just hired its first formal sales team two months prior. "We're very much an enterprise sales motion," she notes. The sales quotas were straightforward: one new client per month initially, ramping to two and then three clients monthly. With 18 engineers and a total team of 23, the company was burning $160,000 monthly in total burn, or about $140,000 in net burn after accounting for the minimal current revenue. This left them with roughly 12 months of runway from their $3.5M raise. On the customer acquisition side, they were still experimenting with ads and retargeting campaigns but hadn't locked in solid unit economics yet—they planned to have reliable metrics ready by February 2021.

Looking ahead, Suzanne was confident the company could hit $1.5M in annual recurring revenue by Q1-Q3 2021, positioning them for a $10M Series A in September 2021. The venture backing had fundamentally changed her playbook compared to bootstrapping her first company. "It took a long time to build that company because it was bootstrapped," she reflects. "Now I wanted to do something venture-backed that goes quickly, so we can go global quickly." With 27% equity each for herself and her co-founder after 50% dilution across their funding rounds, she wasn't motivated by ownership percentage—she was driven by the thrill of seeing a product she'd invented on paper become a global reality.