{"id":336,"date":"2026-05-07T10:29:52","date_gmt":"2026-05-07T10:29:52","guid":{"rendered":"https:\/\/thethriftydev.com\/blog\/openai-anthropic-are-now-consulting-firms\/"},"modified":"2026-05-21T19:08:20","modified_gmt":"2026-05-21T19:08:20","slug":"openai-anthropic-are-now-consulting-firms","status":"publish","type":"post","link":"https:\/\/thethriftydev.com\/blog\/openai-anthropic-are-now-consulting-firms\/","title":{"rendered":"OpenAI & Anthropic Are Now Consulting Firms"},"content":{"rendered":"

Here’s a fun thought experiment: what happens when the companies building your AI models decide they’d also like to be the ones installing them? Not through a partner network, not through certified consultants \u2014 but through their own billion-dollar consulting operations backed by private equity?<\/p>\n

That’s not a hypothetical anymore. In the span of a single week, both OpenAI and Anthropic announced plans to launch separate, PE-backed joint ventures that will essentially function as enterprise AI consulting firms. We’re talking about $4 billion raised by OpenAI for something called “The Deployment Company,” and Anthropic lining up $1.5 billion with Blackstone and Goldman Sachs for a similar play. The companies that make the models now want to deploy them too.<\/p>\n

And if you’re an indie developer, freelancer, or small business owner relying on these APIs to build your products? This affects you way more than you think.<\/p>\n

\"A<\/p>\n

What’s Actually Happening<\/h2>\n

Let’s break down the moves, because there’s a lot of money flying around and the headlines can get confusing.<\/p>\n

OpenAI’s “Deployment Company”<\/strong> raised over $4 billion from 19 investors including TPG, Brookfield, Advent, and Bain Capital, according to The Decoder<\/a>. The venture has a $10 billion pre-money valuation. OpenAI retains majority ownership, and the PE backers get access to their 2,000+ portfolio companies as a built-in customer base. As Reuters reported<\/a>, OpenAI itself is committing up to $1.5 billion in equity to the joint venture.<\/p>\n

Here’s the kicker: TeckNexus reports<\/a> that PE investors are getting a 17.5% guaranteed annual return over 5 years<\/strong>. That’s not a bet on growth. That’s a contractual obligation. Which means The Deployment Company needs to generate serious revenue fast \u2014 and that revenue comes from selling AI implementation services to enterprises.<\/p>\n

Anthropic’s joint venture<\/strong>, as Reuters reported via WSJ<\/a>, is a $1.5 billion enterprise AI services company backed by Blackstone, Hellman & Friedman, and Goldman Sachs. Anthropic will supply applied AI engineers to work alongside the new company’s engineering team. Notably, they’re targeting mid-sized businesses<\/em> \u2014 not just Fortune 500 companies.<\/p>\n

CIO.com frames this<\/a> as “signaling a new phase in the enterprise AI race.” I’d go further \u2014 it’s a fundamental shift in what these companies are<\/em>.<\/p>\n

\"A<\/p>\n

Why This Matters Beyond the Enterprise<\/h2>\n

At first glance, this looks like a big-corporate story. Private equity, Goldman Sachs, $4 billion funds \u2014 what does this have to do with someone building a SaaS tool with the Claude API or running automations on GPT-4?<\/p>\n

Everything, actually.<\/p>\n

When model providers become deployment consultants, three things happen that directly affect the self-serve market:<\/p>\n

First, pricing pressure shifts.<\/strong> These joint ventures need to show revenue. That means aggressively selling implementation packages, managed services, and “AI transformation” engagements. The natural incentive is to make the self-serve experience good enough to hook you, but complex enough that enterprises feel they need the consulting overlay. It’s the classic “free tier gets you in, enterprise contract gets you stuck” playbook.<\/p>\n

Second, the competitive landscape for AI tools changes.<\/strong> As WealthManagement.com notes<\/a>, traditional consulting firms and systems integrators \u2014 think Accenture, Deloitte, McKinsey \u2014 now face direct competition from the model providers themselves. OpenAI already had “Frontier Alliances” with BCG, McKinsey, and Accenture. Now they’re building their own deployment arm. Those partnerships won’t last forever.<\/p>\n

Third, and this is the contrarian take:<\/strong> this could actually be good<\/em> for indie developers. Here’s why.<\/p>\n

\"A<\/p>\n

The Infrastructure Bottleneck Nobody Talks About<\/h2>\n

According to VentureBeat’s coverage of Mistral’s new Workflows launch<\/a>, over 40% of agentic AI projects will be aborted by 2027<\/strong> due to costs and complexity. The agentic AI market is valued at $10.9 billion in 2026, projected to hit $199 billion by 2034 \u2014 but the growth isn’t smooth. The bottleneck isn’t model capability. It’s deployment<\/em>.<\/p>\n

Companies buy GPT-4 or Claude access, get excited in a demo, and then can’t figure out how to integrate it into their actual business processes. Sound familiar? We covered exactly this problem in Why Most AI “Hacks” Fail (And How to Build Workflows That Actually Stick)<\/a> \u2014 the gap between “AI can do this” and “AI is doing this reliably in production” is where most projects die.<\/p>\n

OpenAI and Anthropic see this gap. That’s why they’re launching deployment companies. They know that selling API access alone won’t get them to the revenue numbers their investors expect. They need to capture the implementation budget too.<\/p>\n

But here’s what’s interesting for those of us who build things ourselves: the more these companies focus on enterprise consulting, the more they need a thriving ecosystem of small developers and startups building on their APIs. Enterprise customers want to see that a platform has momentum, that there are tools, integrations, and community around it. Your indie project? It’s marketing for them. Your SaaS tool that uses their API? It’s proof of concept for their next enterprise pitch.<\/p>\n

What It Means for Indie Devs and Small Teams<\/h2>\n

Let me be blunt about the risks and opportunities here.<\/p>\n

The Risks<\/h3>\n