Getting artificial intelligence to actually work inside a large corporation has become so difficult that entire new job categories are emerging to handle it. A newly launched startup called June, backed by Marc Benioff's Time Ventures and supported by tech leaders including Michael Dell and Aaron Levie, just raised $20 million in pre-seed funding to tackle this exact problem. The company's core insight is simple but revealing: AI paradoxically increases demand for professional services rather than reducing it.

Why Can't Companies Just Deploy AI on Their Own?

The challenge isn't building AI agents or language models anymore. The real bottleneck is integrating those tools with the messy reality of existing corporate systems. Most large enterprises run on a patchwork of legacy platforms like Salesforce, ServiceNow, Databricks, and Workday, each storing overlapping or conflicting data in different ways. Before any AI system can create value, someone has to navigate this technical maze.

Efrat Rapoport, June's founder and a former Salesforce executive, explained the core problem: "Before AI can create value, someone has to deal with legacy systems. You have fragmented data across these platforms. You have complex workflows. You have years of technical debt." This reality has spawned an entire category of specialists called forward-deployed engineers, or FDEs, who parachute into companies specifically to get AI systems running.

Efrat Rapoport, June's founder and a former Salesforce executive

"AI, paradoxically, increases the demand for professional services. The industry's answer to AI implementation is, 'let's hire more and more and more people'," said Efrat Rapoport, founder of June.

Efrat Rapoport, Founder and former Salesforce executive, June

Rapoport and her three co-founders, Ohad Hen, Barak Goldstein, and Idan Tsitiat, previously built Bonobo AI, a voice-to-text company acquired by Salesforce in 2019. After years working on Salesforce's AI initiatives, they watched customers struggle repeatedly with the same integration problems, which inspired them to start June.

How Does June's Platform Actually Work?

Rather than requiring companies to hire consultants or forward-deployed engineers, June automates the discovery and planning phase. The platform scans a company's existing systems to map out business processes, identify bottlenecks, and then generate a step-by-step roadmap for deploying AI agents safely and effectively.

The workflow is designed to be transparent and actionable. Instead of handing off a black box to specialized engineers, June gives teams a clear guide that includes specific tasks like removing duplicate database fields or connecting to particular data sources. Once a task is approved, the platform builds the necessary integration automatically.

Steps to Implementing AI Agents in Enterprise Systems

• System Scanning: June's platform analyzes your existing software infrastructure to understand how data flows across Salesforce, ServiceNow, Databricks, Workday, and other platforms your company uses.
• Roadmap Generation: The system automatically creates a step-by-step implementation guide that identifies which duplicate fields need removal, which data sources need connection, and in what order tasks should be completed.
• Automated Building: Once your team approves each task, June builds the necessary integrations and AI agent connections without requiring specialized engineering knowledge.

Paul Akinmade, chief strategy officer at CMG, a major U.S. mortgage lender, experienced the traditional pain point firsthand. After moving his company's software engineering to Claude Code, he hit a wall trying to integrate it with Salesforce. He had publicly committed to deploying 100 agents at Salesforce's annual conference, but the integration challenges made that target look unreachable.

His team spent weeks consulting with architects and forward-deployed engineers without progress. When Akinmade tried June's platform, it provided the visibility and guidance his team needed. Notably, he was able to deploy agents safely even before the official kickoff call with Salesforce.

"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," said Paul Akinmade, chief strategy officer at CMG.

Paul Akinmade, Chief Strategy Officer, CMG

What Does This Mean for the AI Services Industry?

June's funding and early traction suggest that the AI deployment bottleneck is real enough to attract serious venture capital attention. The company raised $20 million without even having a formal pitch deck, according to Rapoport, signaling investor confidence in both the problem and the team's ability to solve it.

Rapoport sees June as complementary to forward-deployed engineers and consultants, but the product's appeal to customers like CMG suggests it may actually reduce demand for those services. Akinmade's explicit preference for an easy-to-use tool over a black box solution points to a broader market shift: enterprises want to own and understand their AI implementations rather than outsource them entirely.

The founding team's track record adds credibility to their vision. After Salesforce acquired Bonobo AI in 2019, the founders spent years inside one of the world's largest enterprise software companies, giving them direct exposure to the exact problems they're now solving. This insider perspective, combined with backing from major figures like Michael Dell and Aaron Levie, positions June as a potential standard-bearer for a new category of AI deployment infrastructure.

As AI adoption accelerates across enterprises, the gap between building AI models and deploying them reliably in production environments continues to widen. June's $20 million raise suggests that venture capital is betting this gap represents a genuine market opportunity, not just a temporary friction point in the AI adoption curve.