AI models are becoming increasingly sophisticated, but the big question remains what exactly adoption will look like in enterprises. To shape that future, labs like Anthropic and OpenAI have launched separate businesses dedicated to placing AI engineers in their customers’ offices. It’s a bet that helping companies understand how to use AI models will be the next trillion-dollar category.
One of those businesses has a name. Ode with Anthropic is a $1.5 billion AI implementation company that AI Lab launched in May as part of a joint venture with Blackstone, Hellman & Friedman, Goldman Sachs and others. This move follows OpenAI’s own take on this, The Deployment Company, which highlights the growing recognition among frontier AI labs that winning enterprise customers requires more than just shipping better models.
Ode was originally invented by Blackstone. Blackstone noticed a gap when it brought together large consulting firms and small AI services boutiques to implement AI across its portfolio companies. One of those boutiques, AI engineering services startup Fractional AI, clearly stood out, and the joint venture acquired it shortly after the announcement. (Fractional ended its 11-month partnership with OpenAI when it was acquired.)
Fractional became the basis for what is now Ode. This is a kind of “large boutique” AI services company. And its leaders have ambitious goals.
“If we execute well, it’s very easy to imagine this becoming a trillion-dollar company one day,” Ode CEO and Fractional co-founder Chris Taylor told TechCrunch in an exclusive interview. “The key challenge for businesses is how to overcome the hyper-growth phase without losing focus on quality.”
Ode currently employs 100 engineers and works closely with Anthropic’s applied AI team to identify where technology can impact different businesses and build systems tailored to each organization’s operations.
Anthropic’s internal team will continue to focus on strategic, mission-aligned deployments, a spokesperson told TechCrunch. The private equity firms backing Ode will pool their portfolio companies into the joint venture as potential customers, but Ode does not intend to limit the sale of its services to those companies.
Taylor said Ord’s ideal customer is one whose CEO is receptive to that promise.
“A lot of the work we do is one or two of the top priorities for the CEO of a company,” Taylor said. “This is the most significant product feature the company will build over the next two years, or re-engineer the most important business process it has.”
Ode operates on the “Claude-first” principle. This means implementing as much of Anthropic’s technology as possible, including features like Slack’s Claude Tag. However, the company will not be limited to Anthropic’s technology; it will also use rival AI products as needed.
Eddie Siegel, chief engineer at Ode and co-founder of Fractional, says the secret to this venture is the quality of implementation and the ability to build custom solutions to business problems.
“I think model selection is important, but that’s not where you spend the majority of your calories,” Siegel says. “This is one element of the system that needs to be designed. It’s like choosing a programming language when building software (…) I don’t define enterprise transformation in terms of choosing Python or Java.”
Taylor added that Ode’s underlying belief is that “non-AI companies can be big winners throughout this AI era if they adopt technology in the right way.” But he said significant help is needed to harness “this magical psychedelic ingredient” of AI and reconnect core business processes and customer experiences to it.
“That requires top-notch applied AI talent, which most companies don’t have,” Taylor said.
Ode executives describe their team as an elite group of generalist software engineers, more than half of whom are former founders, the type of people who, according to Siegel, “can take on very difficult technical problems and at the same time own something end-to-end.” Or, in the words of one Blackstone executive, a team of “adult” engineers, or “special forces,” rather than an army of forward-deployed engineers (FDE).
Demand for such FDE teams far exceeds supply, several people involved in the venture told TechCrunch. Ode’s goal is to maintain its status as a boutique company while continuing to scale internationally. This means performing ongoing assessments to measure the business impact of AI implementation.
But in a world where talented engineering talent is already in short supply, retaining and growing such teams is a major challenge. If becoming an elite applied AI engineer requires entrepreneurial experience, systems-first thinking, AI chops, and enterprise product judgment, can Ode train enough people to meet demand?
Compounding these challenges is the fact that Ode competes not only with OpenAI’s The Deployment Company, but also with consulting giants like Deloitte and Accenture, which have created their own FDE teams.
Siegel isn’t too worried about the shrinking population of adult generalist engineers.
“It has never been easier to be an entrepreneur,” he said. “You learn a lot by trying to solve problems end-to-end, making product-market fits, and changing the direction of the business. You learn a lot there that you can’t learn just by solving narrow problems. That’s a skill set that’s a great fit for Ode.”
Whether enough engineers will participate is an open question. But if Ode and his supporters are right, the next AI race will not just be about the best models, but who can make those models work within the world’s biggest companies.
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