Enterprises are drowning in a paradox: the very AI tools meant to streamline operations are creating a new bottleneck—deployment. A new startup, June, backed by Marc Benioff's Time Ventures, is betting that AI itself can solve this integration crisis. The company emerged from stealth on Monday with a platform designed to automate the messy work of connecting AI agents to legacy systems, a task that has traditionally required armies of specialized engineers. Main Developments June's approach is straightforward: its platform scans a company's existing systems to map business processes, identify bottlenecks, and then automatically generate a step-by-step implementation roadmap for deploying AI agents. The platform can even execute the required tasks, such as removing duplicate database fields or connecting to data sources, with a simple click. According to CEO Efrat Rapoport, a former Salesforce executive, this gives enterprises a clear, automated path to implementation, avoiding the complexity that typically derails AI projects. To fund this vision, June raised $20 million in pre-seed funding, led by Marc Benioff's Time Ventures, with participation from tech luminaries including Michael Dell, Aaron Levie, and George Kurtz. The company declined to disclose its valuation, but Rapoport noted that investor confidence was so high that "we didn't even have a deck for this raise." The founding team—Rapoport, Ohad Hen, Barak Goldstein, and Idan Tsitiat—previously built Bonobo AI, a voice-to-text company acquired by Salesforce in 2019, where they later worked on the tech giant's AI initiatives. Read also: MacBook Air Hit by Global Memory Shortage, Shipments Slip Background The startup's genesis lies in a growing industry trend: the rise of forward-deployed engineers (FDEs), specialists who embed with clients to get AI systems running. While FDEs have become a common solution, they are expensive and often create dependency. Rapoport and her co-founders observed this struggle firsthand while at Salesforce, watching customers grapple with integrating AI into their existing platforms. They concluded that the industry's default response—"let's hire more and more and more people"—was unsustainable. The challenge is rooted in the fragmented state of enterprise IT. Any AI model must work with platforms like Salesforce, ServiceNow, Databricks, and Workday, each with its own data structures and workflows. "You have fragmented data across these platforms. You have complex workflows. You have years of technical debt," Rapoport explained. Building an agent template is the easy part; getting it to function amidst duplicate database fields and conflicting team practices is the real hurdle. Why It Matters June's emergence comes at a pivotal time for the software industry. While the so-called "SaaSpocalypse" has some fearing AI will replace software firms, the reality is that no AI model can yet handle the complexities of a Fortune 500 company's CRM without deep integration. June's platform aims to bridge that gap, potentially reducing the need for FDEs and consultants. For customers like Paul Akinmade, chief strategy officer at CMG, a major U.S. mortgage lender, this is a key selling point. Akinmade, who had struggled to integrate Claude Code with Salesforce, told Rapoport: "If your product requires FDEs, I don't want your product. I've already done that and I'm getting annoyed by it." June's value proposition is not just about cost savings; it's about democratizing AI deployment. By providing a visual roadmap and automated execution, the platform empowers internal teams to implement AI without relying on external experts. This could accelerate AI adoption across industries that lack the resources to hire specialized talent. What's Next June is already gaining traction. CMG, for instance, used the platform to deploy agents safely and efficiently, even before the official kickoff call between the two companies. Akinmade's team had previously spent weeks hitting a wall, consulting architects and FDEs without progress. With June, they gained a clear view of where to deploy agents, helping them move toward a goal of running 100 agents. Looking ahead, June plans to continue refining its platform and expanding its customer base. The company's founders believe that AI-driven deployment is the key to unlocking AI's full potential in the enterprise. As Rapoport put it, the goal is to provide a "full roadmap automatically of what needs to happen step by step for you to actually implement this agent successfully in an enterprise environment." The startup's success will depend on whether it can deliver on that promise at scale.