June emerged from stealth today with a $20 million pre-seed round to make AI adoption simpler.

It’s so hard for big businesses to get AI tools working reliably that whole new organizations of forward-deployed engineers or FDEs— specialists who drop into a company to get its AI systems up and running — are springing up to help them. “AI, paradoxically, increases the demand for professional services,” says Efrat Rapoport, a former Salesforce executive whose new company, June, emerged from stealth Monday morning. “The industry’s answer to AI implementation is, ‘let’s hire more and more and more people.” Rapoport and her three cofounders — Ohad Hen, Barak Goldstein, and Idan Tsitiat — have a different idea about how to bring AI into broader use. To pursue it, the company raised $20 million in pre-seed funding led by Marc Benioff’s Time Ventures, with additional backing from tech luminaries like Michael Dell, Aaron Levie and George Kurtz. The company declined to share its valuation. The four founders previously started Bonobo AI, a pre-transformer language model company that launched a voice-to-text service in 2017. Bonobo AI was snapped up two years later by Salesforce, and the team worked for several years on the tech giant’s AI initiatives before setting out on their own again after watching customers struggle to bring AI into their existing platforms. Their potential was clear enough to their investors, Rapoport says, that “we didn’t even have a deck for this raise.” While the so-called SaaSpocalypse has software firms fearing that AI might replace them, thus far no one is vibe-coding a CRM for a Fortune 500 company. Any AI model brought into a corporate setting still has to work with Salesforce, ServiceNow, DataBricks, Workday, or any of a dozen other data-management platforms. “Before AI can create value, someone has to deal with legacy systems,” Rapoport says. “You have fragmented data across these platforms. You have complex workflows. You have years of technical debt.” Building an agent template is the easy part, she says. The hard part is getting it to work with the mess underneath. “How does an agent know how to operate when you have 10 duplicate [database] fields that say the same thing, and different teams are using them?”