Every company wants to use AI these days. Actually making it work inside a real business? That is a lot harder than it sounds.
Blackstone identified a shortfall after engaging both prominent consulting organizations and small AI service shops to integrate AI into its portfolio businesses. One of those boutiques, Fractional AI, stood out. It had already run an 11‑month partnership with OpenAI, working on real deployment challenges. Blackstone figured it had found something worth scaling.
So Blackstone teamed up with Anthropic, the AI lab behind Claude, and a group of other partners including Hellman & Friedman and Goldman Sachs. Together they created a new company called Ode. The goal is simple: send elite engineers into businesses to figure out how to use Anthropic's AI models, creating systems tailored to each organization's operations.
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Ode's CEO is Chris Taylor, who co-founded Fractional AI. He put it this way: "It's pretty easy to imagine this as a trillion-dollar company someday if we execute well." That is a big number, but the logic is straightforward. If AI is as transformative as everyone thinks, the companies that figure out how to use it right will be the ones that make the money. Ode wants to be the one that helps them get there.
Its chief technologist Eddie Siegel says the real challenge is not the AI models themselves. "I think model selection matters, but it's not where the majority of calories are spent," he said. The hard work is understanding a client's messy data, their broken workflows, and their stubborn business rules - then building something that actually fits.
That requires a rare kind of engineer. Someone who can handle the technical side and also talk to a CEO about what the company really needs. Siegel noted that "it has never been an easier time to become an entrepreneur," but finding people who can operate at that level is still tough. Ode has to compete for talent with OpenAI's own similar company called The Deployment Company, plus the big consulting firms like Deloitte and Accenture that are already hiring forward-deployed engineers.
The rise of Ode points to a shift in how the AI industry is thinking about value. For a while, all the excitement was about building better models. Now frontier AI laboratories are increasingly recognizing that securing enterprise clients demands much more than just releasing improved models.
Chris Taylor said 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." That is worth paying attention to. But there is a catch. "That requires top-caliber applied AI talent, which is not something most companies have," Taylor added. Ode's whole business is built on that shortage.
It remains unclear if a sufficient number of such engineers will emerge. Ode aims to keep expanding, including across borders, while preserving its boutique identity - that is, conducting ongoing assessments to gauge the business effects of AI deployments.
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