June, a startup founded by former Salesforce executives, exited stealth Monday with $20 million in pre-seed funding led by Marc Benioff's Time Ventures to help large enterprises automate the complex process of deploying AI tools within existing corporate systems.
June, an AI startup founded by former Salesforce executives, exited stealth Monday after raising $20 million in pre-seed funding to help large companies navigate the persistent difficulties of deploying AI tools within complex corporate technology stacks.
The round was led by Marc Benioff's Time Ventures, with additional participation from Michael Dell, Aaron Levie, and George Kurtz, according to TechCrunch, which first reported the company's emergence. June declined to disclose its valuation.
The company was founded by Efrat Rapoport and three co-founders — Ohad Hen, Barak Goldstein, and Idan Tsitiat — all of whom previously built Bonobo AI, a pre-transformer language model company that launched a voice-to-text service in 2017 before being acquired by Salesforce two years later. The team spent several years inside Salesforce working on AI initiatives before leaving to start June.
Rapoport, who serves as CEO, said the impetus for the company came from watching enterprise customers struggle to move from AI prototypes to working deployments. "AI, paradoxically, increases the demand for professional services," she said. "The industry's answer to AI implementation is, 'let's hire more and more and more people.'"
The problem she describes is structural. Even when a company settles on an AI model or agent framework, it still must integrate that system with platforms like Salesforce, ServiceNow, Databricks, or Workday — often while contending with years of accumulated technical debt, fragmented data, and duplicated database fields across teams. "Before AI can create value, someone has to deal with legacy systems," Rapoport said.
June's platform attempts to automate the diagnostic and build phases of that process. It scans a company's existing systems to map business processes, identify bottlenecks, and generate a step-by-step deployment roadmap, then executes individual build tasks on demand. "We give you the full roadmap automatically of what needs to happen step by step for you to actually implement this agent successfully in an enterprise environment," Rapoport said.
The startup counts CMG, described as a major U.S. mortgage lender, among its early customers. Paul Akinmade, chief strategy officer at CMG, said his team had moved its software engineering to Claude Code but hit a wall trying to integrate the tool with Salesforce — a problem given that he had publicly committed to running 100 agents at the company. He said weeks of consultations with architects and forward-deployed engineers produced no progress before June cleared the bottleneck.
Akinmade was direct about his requirements before agreeing to pilot the platform. "If your product requires FDEs, I don't want your product," he told Rapoport. "I don't want a black box. I don't want something only certain people can figure out. I want an easy-to-use tool."
The funding round's composition reflects the pedigree the founding team brought to the raise. Rapoport noted that investor confidence was high enough that "we didn't even have a deck for this raise."
June enters a crowded but still-forming market. Enterprises across industries have accelerated AI adoption while simultaneously discovering that the implementation gap between a working prototype and a production-ready deployment remains wide. Whether a platform that automates the connective tissue of that process can scale alongside the pace of enterprise AI spending will become clearer as June moves beyond its early pilots.
TechEchelon Staff bylines are produced collectively by the newsroom for short, breaking, and wire-style coverage. Longer-form reporting is published under the responsible reporter's name.
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