By Titik Puspa 
The complex and often daunting landscape of integrating artificial intelligence (AI) into large enterprises has spurred the emergence of a new breed of tech professionals: forward-deployed engineers (FDEs). These specialists are instrumental in bridging the gap between cutting-edge AI capabilities and the intricate, legacy systems that define most corporate IT infrastructures. Recognizing this burgeoning need and the inherent challenges faced by businesses, a new company named June has emerged from stealth, armed with a substantial $20 million in pre-seed funding. This significant investment, spearheaded by Marc Benioff’s Time Ventures and supported by prominent tech figures like Michael Dell, Aaron Levie, and George Kurtz, signals strong investor confidence in June’s innovative approach to enterprise AI adoption.
Efrat Rapoport, a former Salesforce executive and co-founder of June, articulates the paradox at the heart of the current AI revolution: "AI, paradoxically, increases the demand for professional services." This sentiment underscores the reality that while AI promises transformative efficiencies, its practical implementation within established corporate frameworks is far from straightforward. Many organizations are finding themselves in a perpetual cycle of hiring more personnel to grapple with the complexities of AI deployment, a strategy Rapoport believes is not the most sustainable or effective.
The founding team of June—Rapoport, Ohad Hen, Barak Goldstein, and Idan Tsitiat—is not new to the AI arena. Their prior venture, Bonobo AI, was a pioneering company in pre-transformer language models, launching a voice-to-text service in 2017. Bonobo AI’s success led to its acquisition by Salesforce two years later, where the team spent several years deeply involved in the tech giant’s AI initiatives. It was this firsthand experience, observing customers repeatedly struggle to seamlessly integrate AI into their existing platforms, that inspired their new endeavor. Rapoport notes the remarkable ease of their fundraising process, stating, "we didn’t even have a deck for this raise," a testament to the investors’ faith in their vision and proven track record.
The prevailing narrative in the software industry has often been one of disruption, with concerns that AI might render existing software solutions obsolete. However, the reality for enterprise-level operations is far more nuanced. No AI model, however sophisticated, can unilaterally replace the core functionalities of established platforms like Salesforce, ServiceNow, DataBricks, or Workday. Instead, these AI tools must coexist and integrate with these foundational systems, a process fraught with technical hurdles.
"Before AI can create value, someone has to deal with legacy systems," Rapoport emphasizes. This critical first step involves navigating the labyrinth of fragmented data across disparate platforms, untangling complex, often inefficient workflows, and addressing years of accumulated technical debt. The allure of AI-powered agents, capable of automating tasks and enhancing decision-making, is undeniable. Yet, the true challenge lies not in building these agents, which Rapoport describes as the "easy part," but in ensuring they can operate effectively within the messy, often inconsistent data environments that characterize most large organizations. The question of how an AI agent can function reliably when faced with duplicate data fields or conflicting team usage patterns highlights the depth of the integration problem.
June’s platform is designed to tackle these very challenges head-on. It meticulously scans a company’s existing systems to gain a comprehensive understanding of its business processes. By identifying bottlenecks and inefficiencies, June then constructs more optimized, agent-powered workflows to replace them. These automated processes are designed to seamlessly notify relevant teams through their existing communication channels, fostering smoother collaboration and accelerating adoption. Rapoport elaborates on the platform’s unique value proposition: "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, which is often very complex." June provides a detailed, actionable guide, prompting users with instructions like "Remove these duplicates. Connect to this data source." Users can then click "build" on each task, and June orchestrates the implementation within the organization.
The efficacy of June’s approach is vividly illustrated by the experience of Paul Akinmade, Chief Strategy Officer at CMG, a prominent U.S. mortgage lender. Akinmade had successfully migrated his company’s software engineering efforts to Claude Code, but encountered significant roadblocks when attempting to integrate it with Salesforce. This posed a considerable challenge, especially given a public commitment made at Salesforce’s annual conference to deploy 100 AI agents within a year, a target that was proving difficult to reach. Akinmade’s team spent weeks grappling with the integration issue, engaging with architects, FDEs, and various consultants without achieving meaningful progress. June provided the breakthrough, offering Akinmade’s team a clear path for agent deployment and enabling them to proceed with confidence, even before the official kickoff meeting between the two companies.
Akinmade’s initial skepticism towards solutions that relied heavily on FDEs is particularly telling. He recalls telling Rapoport, "If your product requires FDEs, I don’t want your product. I’ve already done that and I’m getting annoyed by it. 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." June, by offering a more accessible and transparent integration process, evidently met and exceeded this crucial requirement.
While Rapoport positions June as a complementary tool for FDEs and external consultants, its core appeal to customers like Akinmade lies in its potential to reduce or even eliminate the need for such specialized, often costly, external resources. The traditional reliance on FDEs, while effective in many scenarios, can create dependencies and opaque processes that many enterprises are eager to move beyond. June’s ambition is to democratize AI implementation, making it a more manageable and internally driven process for businesses.
The rise of FDEs, as highlighted by their description as "specialists who drop into a company to get its AI systems up and running," signifies a broader industry trend. Companies like CodiumAI, for instance, have also emerged to address the complexities of AI integration, focusing on generating and validating code for AI models. The demand for these roles is a clear indicator that the "out-of-the-box" AI solutions are often insufficient for the nuanced realities of enterprise operations. The challenge is not merely adopting AI, but making it a functional and valuable part of a complex, interconnected business ecosystem.
The $20 million pre-seed funding round for June is a substantial sum, underscoring the significant market opportunity and the investors’ belief in the company’s ability to capture a substantial share of it. The backing from figures like Marc Benioff, the founder and CEO of Salesforce, is particularly noteworthy, suggesting a strategic alignment and potential for future collaboration within the Salesforce ecosystem. Benioff’s investment, through Time Ventures, signals a recognition of the critical need for tools that can bridge the gap between the promise of AI and its practical application within enterprise environments, a domain where Salesforce plays a pivotal role.
The historical context of the founding team’s previous success with Bonobo AI adds another layer of credibility. Bonobo AI’s focus on language models and voice-to-text technology placed them at the forefront of early AI advancements. Their acquisition by Salesforce and subsequent contributions to its AI initiatives provided invaluable experience in navigating the intricacies of enterprise software and AI integration at scale. This deep understanding of both the technical challenges and the business imperatives positions June uniquely to address the market’s unmet needs.
The "SaaSpocalypse" anxiety, referring to fears that AI might disrupt or replace existing Software-as-a-Service (SaaS) providers, has largely subsided for enterprise software. The realization is that AI is more likely to augment and enhance these platforms rather than replace them entirely. However, this augmentation requires sophisticated integration, which is precisely where June aims to excel. The company is not building AI models from scratch; instead, it is focused on the crucial middleware that allows these models to interact effectively with existing enterprise software. This strategic focus on integration, rather than foundational AI development, allows June to leverage the advancements made by other AI companies and focus its resources on solving the complex implementation challenges.
The problem of technical debt, a pervasive issue in enterprise IT, is a significant barrier to AI adoption. Legacy systems, often built and maintained over decades, can be difficult to update, integrate with, or even understand. June’s platform directly confronts this by first analyzing and understanding these existing systems before proposing AI-driven solutions. This diagnostic approach ensures that the AI implementations are grounded in the reality of the company’s current infrastructure, rather than being theoretical solutions that fail to materialize in practice.
The "build" functionality that June offers, allowing users to click and initiate the construction of AI-powered processes, represents a significant step towards user-friendly AI deployment. By abstracting away much of the underlying complexity, June empowers a wider range of users within an organization to participate in the AI implementation process, reducing reliance on highly specialized technical teams and accelerating the time-to-value for AI initiatives. This approach democratizes AI deployment, making it more accessible and manageable for businesses of all sizes, and particularly for those within the Fortune 500 that face the most complex integration challenges.
The narrative of June’s funding and its market positioning suggests a significant shift in how enterprise AI is being approached. Instead of focusing solely on the development of more powerful AI models, the industry is increasingly recognizing the critical importance of effective integration and implementation. Companies like June are at the forefront of this movement, providing the essential tools and expertise to translate the potential of AI into tangible business value within the intricate world of enterprise IT. The substantial funding and the strong backing from industry leaders indicate that June is well-positioned to become a key player in this rapidly evolving landscape, helping businesses unlock the true power of AI by first mastering the art of its integration.
