SableAlpha vs Palantir Foundry for mid-size companies

People ask us this, and it deserves a straight answer, not a sales one. Palantir is the reference point for putting AI safely on company data, and Foundry is what everyone compares against. Here is the comparison as we would give it to a friend who runs finance at a mid-size company, with the caveat that we build Augustine and you should weigh what we say accordingly.

What Palantir Foundry is built for

Foundry is built to integrate a whole company's data. Its core idea is the ontology: data from many systems is joined into one model of the company's objects, their properties and their relationships, and applications, analytics and AI workflows are built on top of that model. It is mature, it is proven at very large scale, and it is used by governments and some of the largest companies in the world.

That strength shapes how it is bought and run. Foundry rollouts are typically company-wide, involve Palantir's own engineers working alongside the buyer for an extended period, and are priced and contracted accordingly. Palantir's public materials describe a base weighted toward large enterprises and government, and that is where its depth pays for itself.

None of that is a criticism. If you are a very large organization with hundreds of source systems and a mandate to build one operational model of the whole company, Foundry is a serious answer, and there are few others at that scale.

What Augustine is built for

Augustine starts from a much smaller place. A finance team at a mid-size company already uses a commercial AI model, usually through a chat window, and nothing checks what it says against the books. Augustine is that check. The model drafts, written rules compare the draft with the company's own records, and an authorized person approves every change.

It does not ask you to move your data or rebuild anything. It works inside the tools the team already has: Jira, Excel, Slack, a QuickBooks Online or Xero export, and the documents you upload. Getting started needs an export, a few documents, and two hours over two weeks.

The practical differences

• Starting unit. Foundry starts from the whole data estate. Augustine starts from one kind of work: the payables and planning questions a finance team answers every week.
• What you are buying. Foundry is a foundation that applications are built on. Augustine is a checking layer around a model you could already be using.
• Shape of the work. Foundry rollouts are typically large and long, with a substantial services component. Getting Augustine onto your data takes two hours of your time over two weeks, and it stops whenever you ask.
• Maturity. Foundry has run at the largest scale for well over a decade. Augustine comes from a young company, has been measured on practice data, and no real company's books have run through it yet. That gap is real, and we say so.

How to tell which question you are asking

If your question is how to build a single operational model of your whole company, you are asking a Foundry question, and you should also look at the other large data vendors.

If your question is how to let your finance team keep using AI without a wrong answer becoming a wrong payment, you are asking a much narrower question that does not require a company-wide program. That is the question Augustine is built to answer.

The two are not exclusive. A company can run a broad internal data program and still want a rule check in front of every AI-assisted change. But if you have to pick a place to start, start with the question, not the vendor.

Where SableAlpha stands

Everything above about Augustine reflects what is built as of the date on this note. The measured figures are on the front page with their caveats. If you want to see it, book a demo.