According to a report by Rebecca Bellan on TechCrunch, leading artificial intelligence labs and companies now realize that the precise way large enterprises will adopt this new technology remains one of the central and most intriguing questions in the market. To actively shape the future of enterprise adoption, leading labs like Anthropic and OpenAI have recently set up entirely separate and independent businesses, whose sole purpose is to send and deploy expert AI engineers directly inside their clients' offices. This strategic move reflects a shared, broad industry bet: the assumption that providing close assistance to businesses and cracking how they should use AI models is the next business category to reach a trillion-dollar valuation.
One of these companies recently received its official name: Ode with Anthropic. This is an AI implementation and integration company valued at $1.5 billion. The company was launched in May as part of a joint venture established by the AI lab Anthropic alongside investment giant Blackstone, Hellman & Friedman, investment bank Goldman Sachs, and other financial partners. The move follows a similar version of this initiative by OpenAI, known as The Deployment Company, thereby highlighting the growing recognition among leading AI labs that acquiring and retaining enterprise customers today requires far more than just launching and developing improved language models.
The Birth of a $1.5 Billion Implementation Company
The new joint venture, Ode, was originally conceived by the private equity group Blackstone. The investment giant identified a fundamental and significant market gap when it tried to enlist large consulting firms alongside small boutique companies specializing in artificial intelligence to implement practical AI solutions across its numerous portfolio companies. During these searches and trials, one small boutique company stood out in particular—an AI engineering services startup called Fractional AI. Impressed by its performance, the joint venture decided to acquire the startup Fractional AI very shortly after the official announcement of its formation.
The surprising acquisition led Fractional AI to end an 11-month business partnership it had with rival company OpenAI. Fractional effectively became the core foundation and infrastructure of what is now known as Ode—defined by its leaders as a kind of "scaled boutique" (scaled boutique) AI services company. The executives of the new company set highly ambitious goals for the near and distant future. As Chris Taylor, CEO of Ode and co-founder of Fractional, stated in an exclusive interview with TechCrunch: "It’s pretty easy to imagine this as a trillion-dollar company someday if we execute well." Taylor added that the core challenge of the business now is figuring out how to navigate the rapid hyper-growth phase without losing an uncompromising focus on quality of service and execution.
The Unique Collaboration and "Claude-First" Principle
As of the time of the report, Ode employs approximately 100 expert engineers and works very closely with Anthropic's internal applied AI team. This collaboration is designed to pinpoint exactly where and at which endpoints the technology can deliver maximum business and operational impact for different companies, and to create custom systems tailored to the specific needs of each organization. An Anthropic spokesperson told TechCrunch that Anthropic’s internal team will continue to focus on strategic, mission-aligned deployments unique to the lab's core tasks.
The private equity firms backing the Ode venture are expected to direct their many portfolio companies to the joint venture as preferred potential clients, though it was explicitly emphasized that Ode will not restrict the sale of its engineering services solely to companies held in those firms' investment portfolios. According to CEO Taylor, the ideal client for Ode is one whose CEO fully believes in and is deeply committed to the promise of AI technology. "A lot of the work that we're doing is the top one or two priority for the CEO of the company," Taylor said. He explained that this is usually either the most important product feature the company plans to develop and build over the next two years, or, alternatively, the restructuring of the most important business process in their organization.
The joint venture will operate under a clear guiding principle of "Claude-first" (Claude-first). This means that Ode engineers will aim to implement Anthropic’s various technologies, including specific features like Claude Tag within the Slack platform, in any project where it is feasible and beneficial to the client. However, it was clarified that the company is not exclusively and absolutely limited to Anthropic's technology alone, and will use AI products from competing companies as necessary and according to the specific needs of different projects.
Implementation Quality vs. Model Selection
Eddie Siegel, Chief Technology Officer of Ode and co-founder of Fractional, explained that the unique competitive advantage of the new venture lies in its quality of implementation and the possibility of building customized solutions for complex business problems. "I think model selection matters, but it’s not where the majority of calories are spent," Siegel said. He compared the choice of a language model to choosing a programming language during software development: "It's just one ingredient in a system that has to be engineered. It’s like the choice of programming language when you build a piece of software. I would not define an enterprise transformation in terms of whether they choose Python or Java."
Taylor added that the founding belief behind Ode is that non-AI or technology companies are going to be among the great winners of the current AI era, provided they adopt the technology in the right and smart way. However, he emphasized that taking AI—which he described as a "magic, hallucinating ingredient"—and rewiring core business processes or customer experiences with it is a complex task that requires significant external help and support. "That requires top-caliber applied AI talent, which is not something most companies have," Taylor concluded.
Human Capital: Recruiting "Special Forces" Engineers
Ode's executives describe the engineering team they are assembling as an elite and select group of top-tier generalist software engineers, with over half of them being former startup founders. Eddie Siegel described them as people capable of "juggling a really challenging technical problem, but also owning something end-to-end." One Blackstone executive defined it even more precisely, calling them a team of "grown-up" and experienced engineers who represent the "special forces," in contrast to a large army of forward-deployed engineers (FDEs).
As several sources involved in the venture told TechCrunch, the demand for such experienced engineering teams currently far outstrips the market supply. Ode's official goal is to continue scaling and growing, including expanding to additional international markets, while tightly maintaining its positioning as an elite boutique firm. The practical meaning of maintaining this positioning is running constant and ongoing evaluations to prove and measure the actual business impact of the AI implementations it develops for its clients.
Growing Competition in the AI Implementation Engineering Market
In a world where top engineering talents are already a scarce and expensive resource, maintaining and growing such a team presents a real and significant challenge for the venture. If becoming an elite applied AI engineer requires entrepreneurial experience, systems-first thinking, advanced AI capabilities, and deep enterprise product judgment, the question remains whether Ode can train and recruit enough people to meet the growing market demand. This difficulty is further amplified by the fact that Ode will compete in the field not only with OpenAI's implementation company, known as The Deployment Company, but also with veteran consulting giants like Deloitte and Accenture, which have already established their own forward-deployed engineering (FDE) teams.
Nonetheless, CTO Siegel is not overly worried about a dwindling pool of experienced generalist engineers. "It has never been an easier time to become an entrepreneur," Siegel said. He explained that "You learn so much by trying to own problems end-to-end, going to try and get product-market fit, and move the needle on a business. You learn a lot there that you don’t learn from just solving a narrow problem. That’s the skill set that fits really well with Ode."
Will a sufficient number of such high-quality engineers actually join the venture in the future? This remains an open question. But if Ode and the major investors backing it are correct in their assessments, the next great AI race will not be about developing the best models, but about who can successfully implement and put those models to work inside the world's largest companies.