Two labs, two joint ventures, one bet
Anthropic and OpenAI are bundling software and services. The interesting question isn't whether that works. It's whose side of the line the trust ends up on.
On Monday, Anthropic announced a joint venture with Blackstone, Hellman & Friedman, and Goldman Sachs. A $1.5B vehicle, with $300M committed by each of the three. Hours later, OpenAI’s parallel deal leaked: $4B at a $10B valuation, with TPG, Brookfield, Advent, and Bain. Different cap tables, no investor overlap, same shape.
Both vehicles do the same thing. They take the Palantir playbook off the shelf. Capital from asset managers, deployed as engineers who sit next to clients and build the workflows the model is supposed to inhabit. Anthropic’s own description is honest about it: “an engagement might begin with the company’s engineering team sitting down with clinicians and IT staff to build tools that fit into the workflows staff already use.”
This is a real shift. The labs that spent two years insisting they were just APIs are now showing up with people. Which is, finally, an honest answer to the question every enterprise buyer has been asking. Who is going to make this actually work in our environment?
We built Aimable on the same observation. Software alone does not get a regulated bank, a healthcare provider, or a 200-person SaaS to run AI on their real workflows. You need the software, and you need humans who can sit in the room and configure it for what the team actually does. So we agree with the bet. Software plus services is how AI lands in organisations that have something to lose.
Where we diverge is the line of trust.
If your forward-deployed engineer works for Anthropic, the trust sits on Anthropic’s side. If they work for OpenAI’s new entity, the trust sits there. You inherit a model roadmap, a data-handling posture, a zero-retention promise, and an exclusivity gravity that gets stronger every quarter. When that model is deprecated, when the pricing changes, when the legal posture shifts, the cost of unwinding is whatever your team built on top of it.
We start from the other side. Aimable installs in your environment. The Workbench is what your team opens instead of ChatGPT. The Platform behind it sits between your people and any AI model. OpenAI today, Anthropic tomorrow, a local model when the conversation is too sensitive to leave the building. Your services come from us, but your data, your logbook, and your rules stay on your side. Switching the model underneath is two lines of code, not a migration.
That is the part of the bundle worth being model-agnostic about. The model is a component. The trust layer is not.
This is not a critique of the JVs. They are going to do well, and forward-deployed engineering is the right shape of the work. We just think the engineers should be on a team that doesn’t also own the model.