AI NewsAnthropic, Blackstone bet the next trillion-dollar AI business is implementation, not just models

Anthropic, Blackstone bet the next trillion-dollar AI business is implementation, not just models

8:40 PM IST · July 15, 2026

AI models are becoming ever more capable, but exactly what enterprise adoption will look like remains a big question. In a bid to shape that future, labs like Anthropic and OpenAI havespun up separate businessesdedicated to deploying AI engineers to their customers’ offices — a bet that assisting businesses in figuring out how to use their AI models is the next trillion-dollar category. One of those businesses now has a name: Ode with Anthropic is the $1.5 billion, AI implementation company that the AI lab launched in May as part of a joint venture with Blackstone, Hellman & Friedman, Goldman Sachs, and others. The move follows OpenAI’s own take on this, The Deployment Company, underscoring a growing acknowledgement among frontier AI labs that winning enterprise customers requires far more than shipping better models. Ode was originally conceived by Blackstone, which noticed a gap when it had roped in 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, apparently stood out, and the joint venture acquired the startup shortly after it was announced. (Fractional ended an 11-month partnership with OpenAI when it was acquired.) Fractional has become the foundation of what is now Ode — a kind of “scaled boutique” AI services firm. And its leaders have ambitious goals. “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 tech can have an impact on different businesses, and create 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 funnel their own portfolio companies to the joint venture as potential customers, though Ode will not limit sales of its services to those companies. For Ode, an ideal customer is one whose CEO buys into the 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 will operate under a “Claude-first” principle, meaning it will implement Anthropic’s technology, including features likeClaude Tag in Slack, whenever possible. The company isn’t limited to Anthropic’s technology, though, and will use rival AI products if needed. Eddie Siegel, Ode’s chief technologist and a Fractional co-founder, says the venture’s secret sauce is its quality of implementation, and the ability to build custom solutions for 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 the founding belief behind Ode is that “non-AI companies are going to be among the big winners of this whole 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 a lot of 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 — the kind of people who can “juggle a really challenging technical problem, but also own something end-to-end,” per Siegel. Or as one Blackstone executive put it: a team of “grown-up” engineers, the “special forces” rather than an army of forward-deployed engineers (FDEs). As several people involved in the venture told TechCrunch, demand for such FDE teams far outstrips supply. Ode’s goal is to continue scaling, internationally too, while maintaining its boutique firm positioning — in other words, 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 experience as an entrepreneur, systems-first thinking, AI chops, and enterprise product judgement, would Ode be able to 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 likeDeloitteandAccenture, which have created their own FDE teams. Siegel isn’t too worried 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 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, but about who can successfully put those models to work inside the world’s largest companies.