Anthropic and Blackstone bet $1 trillion AI prize is in implementation

Advanced AI models are growing more powerful by the quarter, but the path to widespread enterprise adoption remains unclear. To help shape that trajectory, frontier labs like Anthropic and OpenAI have launched separate divisions focused on deploying AI engineers directly into customer offices. This signals a major strategic bet: that helping companies figure out how to actually use these models could be the next trillion-dollar opportunity.

That bet now has a name. Ode with Anthropic is a $1.5 billion AI implementation company formed in May through a joint venture with Blackstone, Hellman & Friedman, Goldman Sachs, and others. The move mirrors OpenAI’s own enterprise push with The Deployment Company, reflecting a growing consensus among leading AI labs that winning corporate clients demands far more than just releasing better models.

Blackstone originally conceived Ode after identifying a gap when it tried to bring in both large consulting firms and smaller AI services boutiques to implement AI across its portfolio companies. One boutique, the AI engineering startup Fractional AI, stood out. The joint venture acquired Fractional shortly after announcing Ode, ending an 11-month partnership the startup had with OpenAI.

Fractional now forms the core of Ode, which its leaders describe as a kind of “scaled boutique” AI services firm. Their ambitions are sizable.

“It’s pretty easy to imagine this as a trillion-dollar company someday if we execute well,” Chris Taylor, CEO of Ode and co-founder of Fractional, told TechCrunch in an exclusive interview. “The key challenge of the business is how do you go through that phase of hyper growth without losing the emphasis on quality?”

Ode currently employs 100 engineers and works closely with Anthropic’s applied AI team to identify where the technology can make a real difference for specific businesses, building custom systems tailored to each organization’s operations.

Anthropic’s internal team will continue focusing on strategic, mission-aligned deployments, a spokesperson confirmed. The private equity firms backing Ode will direct their own portfolio companies to the joint venture as potential customers, though Ode will not limit its services to those firms.

For Ode, the ideal customer is one whose CEO genuinely believes in the technology’s promise, according to Taylor.

“A lot of the work that we’re doing is the top one or two priority for the CEO of the company,” Taylor said. “It’s the most important product feature that the company is going to build over the course of the next two years, or it’s reworking the most important business process they have.”

Ode operates under a “Claude-first” principle, meaning it will implement Anthropic’s technology, including features like Claude Tag in Slack, whenever possible. The company is not locked into Anthropic’s ecosystem, however, and will use rival AI products when necessary.

Eddie Siegel, Ode’s chief technologist and a Fractional co-founder, says the venture’s secret sauce is its quality of implementation and ability to build custom solutions for real business problems.

“I think model selection matters, but it’s not where the majority of calories are spent,” Siegel said. “It’s 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 companies are going to be among the big winners” of this entire AI moment if they adopt the technology the right way. But to take AI, “this magic, hallucinating ingredient,” and rewire core business processes or customer experiences with it requires substantial help, he said.

“That requires top-caliber applied AI talent, which is not something most companies have,” Taylor said.

Ode’s executives describe their team as elite generalist software engineers, over half of whom are former founders. These are people who can “juggle a really challenging technical problem, but also own something end-to-end,” per Siegel. One Blackstone executive called them a team of “grown-up” engineers, the “special forces” rather than an army of forward-deployed engineers.

As several people involved in the venture told TechCrunch, demand for such forward-deployed engineering teams far outstrips supply. Ode’s goal is to continue scaling, including internationally, while maintaining its boutique positioning. That means running constant evaluations to measure the business impact of AI implementations.

But in a world where top engineering talent is already scarce, maintaining and growing such a team presents a real challenge. If becoming an elite applied AI engineer requires entrepreneurial experience, systems-first thinking, AI expertise, and enterprise product judgment, can Ode train enough people to meet demand?

Compound those difficulties with the fact that Ode will be competing not only with OpenAI’s The Deployment Company, but also with consulting giants like Deloitte and Accenture, which have built their own forward-deployed engineering teams.

Siegel is not overly concerned about a dwindling pool of grown-up generalist engineers.

“It has never been an easier time to become an entrepreneur,” he said. “You learn so much by trying to own problems end-to-end, going to try and get product-market fit, 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.”

Whether enough of those engineers will actually show up remains an open question. But if Ode and its backers are right, the next great AI race won’t just be about the best models. It will be about who can successfully put those models to work inside the world’s largest companies.