Anthropic backs Ode to sell AI implementation at scale

Ode bets enterprise AI will be won in deployment

Anthropic and a group of financial backers are betting that the biggest business in enterprise AI won’t be model development, but implementation.

The new company, Ode with Anthropic, is a $1.5-billion AI implementation firm launched in May as a joint venture with Blackstone, Hellman & Friedman, Goldman Sachs and others. The move mirrors OpenAI’s own effort, The Deployment Company, and highlights a growing view among frontier labs that selling access to models is only part of the enterprise equation.

How Ode came together

According to TechCrunch, Blackstone originally conceived Ode after seeing a gap in the market while trying to roll out AI across its portfolio companies. Large consulting firms and smaller AI services boutiques were involved, but one startup stood out: Fractional AI.

The joint venture acquired Fractional AI shortly after it was announced. TechCrunch reports that Fractional had ended an 11-month partnership with OpenAI when it was acquired.

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That startup is now the base for Ode, which its leaders describe as a scaled boutique AI services firm.

“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?”

What the company actually does

Ode currently employs 100 engineers. It works closely with Anthropic’s applied AI team to identify where the technology can affect a business, then builds systems tailored to that company’s operations.

TechCrunch reports that Anthropic’s internal team will remain focused on strategic, mission-aligned deployments.

The private equity firms backing Ode will also steer their own portfolio companies toward the venture, though Ode is not restricting itself to those customers.

For Taylor, the best customer is one where the CEO is fully committed.

“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.”

Claude-first, but not Claude-only

Ode will operate under a “Claude-first” principle. That means it will use Anthropic’s technology, including tools such as Claude Tag in Slack, whenever possible.

But the company is not locked to Anthropic alone. If a rival product is a better fit, Ode says it will use that instead.

That flexibility fits with how its executives describe the job. Eddie Siegel, Ode’s chief technologist and a Fractional co-founder, told TechCrunch that model choice matters, but it is not the core of the work.

“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.”

The real constraint: people

Ode’s pitch rests on talent as much as software. Taylor said the broader thesis 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 rewiring core business processes around what he called “this magic, hallucinating ingredient” takes specialized help.

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

Executives describe the team as elite generalist software engineers, with over half coming from founder backgrounds. One Blackstone executive described them to TechCrunch as “grown-up” engineers and the “special forces” rather than an army of forward-deployed engineers.

That creates the central challenge for the business. Demand for these teams already exceeds supply, and Ode is trying to scale internationally while keeping its boutique positioning and continuously measuring the business impact of deployments.

It is also entering a crowded field, competing not only with OpenAI’s The Deployment Company, but also with consulting firms such as Deloitte and Accenture, which have built their own forward-deployed engineering teams.

Siegel said he is not overly concerned about the talent pipeline.

“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 exist to meet demand is still unclear. But if Ode and its backers are right, the next major enterprise AI battle may hinge less on who builds the best models than on who can make them work inside the world’s biggest companies.