The capabilities of large AI models continue to evolve and improve, yet a major challenge persists for companies: how to practically implement and apply this technology. To capture this future market, AI labs like Anthropic and OpenAI have established dedicated business units, deploying specialized AI engineering teams directly into client companies to provide implementation services. Their assessment is that helping enterprises deploy AI models will create the next trillion-dollar industry.
One such implementation services firm has now been officially named: Ode with Anthropic. This AI implementation specialist, valued at $1.5 billion, was formed as a joint venture by Anthropic in May this year, in partnership with institutions including Blackstone Group LP (NYSE: BX), Hellman & Friedman, and Goldman Sachs. This follows a similar move by OpenAI with its entity The Deployment Company, a trend that underscores a consensus among leading AI labs: winning enterprise clients requires far more than just releasing more powerful models.
The concept for Ode originated with Blackstone Group LP. While implementing AI projects for its portfolio companies, Blackstone Group LP collaborated with both large consulting firms and smaller, specialized AI boutiques, identifying a significant gap in the market. One AI engineering startup, Fractional AI, performed exceptionally well. Following the joint venture's announcement, it was swiftly acquired. Prior to the acquisition, Fractional had just concluded an 11-month collaboration with OpenAI.
Fractional AI forms the core foundation of Ode, enabling the creation of a scaled, high-quality AI services team. The company's management has set ambitious growth targets.
In an exclusive interview with TechCrunch, Ode's CEO and Fractional co-founder, Chris Taylor, stated: "If we execute well, this company has a real opportunity to become a trillion-dollar business. The biggest challenge for this service is scaling rapidly without compromising on quality."
Ode currently employs 100 engineers who work in deep collaboration with Anthropic's applied AI team. They explore AI application scenarios across different industries and build custom systems tailored to each client's specific business processes.
A spokesperson for Anthropic told TechCrunch that its internal team will continue to focus on strategic AI implementation projects aligned with its core mission. The private equity firms investing in Ode will refer their portfolio companies as potential clients, but Ode's business will not be limited to these firms.
Taylor indicated that Ode's ideal clients are companies whose CEOs are fully convinced of AI's value.
"The projects we take on are typically the CEO's top one or two strategic priorities—either the most important product feature to build in the next two years, or re-architecting a core business process," he said.
Ode operates on a principle of preferentially using Claude, aiming to implement Anthropic's technology wherever possible, including features like Claude's integration into Slack. However, it is not restricted to Anthropic's products and will incorporate competing AI tools when necessary.
Ode's CTO and Fractional co-founder, Eddie Segal, explained that the joint venture's core competitive advantage lies in the quality of its delivery and its ability to craft solutions for diverse business pain points.
"Model selection is important, but it's not where the majority of the effort goes. It's just one component in the entire engineering system, akin to choosing a programming language for software development... The success of a digital transformation never hinges on whether you pick Python or Java," Segal noted.
Taylor added that the core motivation for founding Ode was: "If AI is implemented correctly, non-tech companies will be among the biggest winners of this AI wave." However, to use this "tool with generative hallucination properties" to re-architect core processes and reshape customer experiences, companies require significant external expertise.
"The vast majority of companies lack top-tier applied AI talent," Taylor stated.
Ode's management defines its team as elite, full-stack software engineers, with over half having startup experience. Segal explained that such talent can tackle complex technical challenges while independently managing entire project lifecycles. A Blackstone Group LP executive described the team as a "special forces" unit of seasoned, senior engineers, rather than a large, generic contingent of outsourced developers.
Multiple individuals involved in the joint venture told TechCrunch that market demand for outsourced AI engineering teams already far exceeds supply. Ode plans to expand domestically and internationally while maintaining its boutique positioning—meaning it will continuously quantify the actual business value delivered by AI implementations.
However, top engineering talent is inherently scarce, making building and scaling such a high-caliber team a genuine challenge. Elite applied AI engineers need a blend of startup experience, systems thinking, AI technical skills, and product judgment for the enterprise. Whether Ode can cultivate enough of this talent to meet market demand remains an open question.
Beyond this, Ode faces multiple layers of competition. Its rivals include not only the implementation company launched by OpenAI but also consulting giants like Deloitte and Accenture, which have already established their own outsourced AI engineering teams.
Segal, however, is not overly concerned about a shortage of senior, versatile engineers.
"The barrier to starting a company has never been lower. Running a full project, achieving product-market fit, and driving growth teaches you a massive amount that you can't learn just by solving a single technical problem. That skillset is exactly what fits the needs of Ode's business," he said.
Whether such high-end engineers will continue to emerge in sufficient numbers remains to be seen. But if the judgment of Ode and its investors proves correct, the next phase of competition in AI will shift from a race for model performance to a contest over who can truly integrate AI technology into the business systems of the world's largest corporations.
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