Salesforce veterans raise $20 million pre-Seed from Marc Benioff and Michael Dell to tackle AI’s enterprise bottleneck
June AI, founded by the team behind Bonobo AI after five years at Salesforce, is building AI agents to automate the costly software implementation work holding back enterprise AI adoption.
June AI has emerged from stealth with $20 million in pre-Seed funding from a group of strategic investors led by TIME Ventures, the investment arm of Salesforce CEO and founder Marc Benioff.
The round includes participation from several prominent technology executives, including Michael Dell, founder, chairman and CEO of Dell Technologies; Diane Greene, co-founder and former CEO of VMware; Aaron Levie, co-founder and CEO of Box; and George Kurtz, founder and CEO of CrowdStrike, alongside SV Angel, Conviction Embed, Abstract, A*, Vesey Ventures and other venture firms.
The company, which is developing AI tools for enterprise software implementation, is targeting what it describes as one of the biggest but least visible barriers to AI adoption: the difficulty of integrating new AI capabilities into the complex software systems that run large organizations.
June AI was founded in late 2025 by Efrat Rapoport, CEO; Idan Tsitiat, CTO; Barak Goldstein, president; and Ohad Hen, chief architect. The team previously founded Bonobo AI, a conversational intelligence company that was acquired by Salesforce in 2019.
Following the acquisition, the founders spent five years inside Salesforce, with Rapoport serving as VP Product Management and Head of Salesforce Israel R&D. The team worked on AI products and gained firsthand exposure to the challenges large companies face when attempting to transform their operations with new technologies.
The experience led them to focus on a recurring problem: organizations are investing heavily in AI, but often struggle to implement it across existing systems, fragmented data environments and complex business processes.
Large organizations rely on dozens of software platforms to manage their operations, including systems from Salesforce, ServiceNow, Workday, Oracle, SAP and Microsoft. But configuring those systems, integrating them and adapting them as business needs change often requires large teams of consultants, long implementation cycles and significant manual work.
June AI is targeting this implementation layer.
According to Grand View Research, the global system integration market is expected to reach $1.3 trillion by 2033, highlighting the scale of the challenge companies face in connecting and maintaining increasingly complex technology environments.
In an interview with Calcalist, Rapoport said that companies have accumulated years of technical debt through continuous changes and integrations.
“Everyone buys these systems, but they need to be implemented, integrated into business processes and kept aligned with the business over time,” Rapoport said. “Today, this is a process that takes a lot of time and is still largely done manually.”
She said the rapid adoption of AI has made the challenge even more significant.
“AI has created more demand for professional services, not less,” Rapoport said. “Companies are investing heavily in AI transformation, but the work required to implement those changes is still highly manual. Teams have to deal with legacy systems, fragmented data, complex workflows and years of technical debt before AI can create real value.”
June AI’s platform is designed to automate parts of the work traditionally performed by forward-deployed engineers, implementation teams and system integrators.
The company’s approach begins with process mining, analyzing how a business actually operates through the systems it already uses. The platform then identifies opportunities for improvement, implements changes and deploys AI solutions designed around the organization’s specific workflows.
Unlike many AI tools that focus on individual applications, June AI aims to understand how different systems interact and how changes in one part of an organization affect others.
The company says its platform can work across existing enterprise environments, including data platforms such as Snowflake and Databricks, while remaining integrated with the broader software stack.
The goal is to reduce the time required to move from identifying an AI opportunity to deploying a working solution inside an organization.
“Every company wants to become an AI company, but the hard part is not the demo,” Rapoport said. “The hard part is changing the systems, workflows and operating models that already exist inside the enterprise.”
The challenge June AI is targeting has become increasingly visible across the technology industry.
Even companies developing leading AI models have created dedicated teams focused on helping customers deploy AI systems. OpenAI has established deployment teams, Anthropic has launched enterprise AI services, and AWS operates professional services teams focused on implementation.
The trend reflects a broader reality: advanced AI models alone are not enough to transform businesses. Organizations still need help adapting their internal systems, workflows and processes before they can benefit from the technology.
June AI argues that the next stage of enterprise AI adoption will depend not only on the quality of AI models, but also on the ability to deploy them effectively inside companies.
“The next phase of enterprise AI will be defined as much by implementation, migration and adoption as by the sophistication of the AI itself,” Rapoport said.
