Anthropic and OpenAI are moving toward a more hands-on model for selling artificial intelligence to businesses, with both companies tied to new ventures aimed at deploying enterprise AI services more directly.
Anthropic announced on Monday that it is forming a new AI services company with Blackstone, Hellman & Friedman, and Goldman Sachs as founding partners. The venture is designed to help mid-sized companies adopt Claude in core business operations, with Anthropic applied AI staff working alongside the new company’s engineers.
The company said the venture is also backed by a wider group of alternative asset managers and investment firms, including General Atlantic, Leonard Green, Apollo Global Management, GIC, and Sequoia Capital. The Wall Street Journal reported that the new business is valued at $1.5 billion and includes $300 million commitments from Anthropic, Blackstone, and Hellman & Friedman.
Why the enterprise AI services push matters
The timing is notable because OpenAI is reportedly preparing a similar move. Bloomberg reported that OpenAI has been raising funds for a new venture called The Development Company, aimed at enterprise AI deployment. According to that report, the OpenAI-linked venture would be larger than Anthropic’s, seeking $4 billion from 19 investors at a $10 billion valuation.
Reported investors in the OpenAI effort include TPG, Brookfield Asset Management, Advent, and Bain Capital. The investor lists, at least as reported so far, do not appear to overlap with the group backing Anthropic’s new venture.
AI Engineering: Building Applications with Foundation Models
This technical guide is a better fit for engineering and product teams that want to understand how foundation-model applications are actually designed, evaluated, and maintained.
As an Amazon Associate I earn from qualifying purchases.
The shared idea is straightforward: AI labs want more than software subscriptions and API usage. They want structured sales and implementation channels that can move frontier AI tools into real business processes. Alternative asset managers, private equity firms, and other large investors can help provide those channels because they already have relationships with broad portfolios of companies.
For buyers, that could mean more AI offerings arrive through boardrooms, portfolio operations teams, and consulting-style engagements rather than through normal software procurement alone. For investors, the appeal is also clear. If portfolio companies spend more on AI implementation, the firms backing the service ventures may capture value on both sides of the transaction.
The forward-deployed engineer model comes to AI labs
Both efforts point toward a model that looks less like selling a standard SaaS product and more like embedding engineers close to the customer. Palantir helped popularize the forward-deployed engineer approach, where technical teams work directly with clients to tailor software to messy operational needs.
Anthropic described a similar pattern for its new company. A typical engagement could start with engineers sitting down with a customer’s staff to understand where Claude might fit into existing workflows. In one healthcare example, the work could involve clinicians and IT teams identifying bottlenecks in documentation, coding, prior authorizations, or compliance reviews.
That kind of deployment is labor-intensive. It requires more engineering time, more customer context, and more patience than a simple license sale. It also reflects a practical reality of enterprise AI: many companies are interested in AI, but lack the internal teams needed to turn model access into working systems.
Competing in the Age of AI
This book can help business leaders think beyond AI tools and consider how AI changes processes, scale, and organizational design.
As an Amazon Associate I earn from qualifying purchases.
Anthropic positioned the new firm as an addition to its existing partner ecosystem rather than a replacement for large consulting and systems integration relationships. The company already works with firms such as Accenture, Deloitte, and PwC through the Claude Partner Network, while the new venture appears focused on expanding delivery capacity for mid-sized businesses.
AI labs are pairing capital with distribution
The service ventures also arrive as the largest AI labs continue to raise enormous sums of money. OpenAI announced at the end of March that it had closed $122 billion in committed capital at an $852 billion post-money valuation. Anthropic has also been tied to a major funding round, with TechCrunch reporting that it was in the final stages of raising $50 billion at a $900 billion valuation.
Those figures underline how much capital the AI sector is consuming as model companies compete on infrastructure, product development, and enterprise distribution. The new service ventures fit into that larger pattern. They are not just about selling more AI tools. They are attempts to build repeatable routes into companies that may otherwise struggle to deploy AI in useful, measurable ways.
For enterprise buyers, the key question will be whether these ventures can deliver practical results instead of expensive pilots. The promise is more direct engineering support and AI systems shaped around actual workflows. The risk is that companies end up locked into vendor-led implementation paths before they fully understand the costs, limits, and governance requirements of the technology.
Either way, Anthropic and OpenAI appear to be moving beyond the idea that enterprise AI adoption will happen mostly through self-serve tools. The next phase of competition may depend as much on services, distribution, and implementation talent as on the models themselves.