Palantir Proof of Value: How to Test Foundry and AIP Before You Buy a License

You can test Palantir Foundry and AIP on your own data before you commit to a platform license, and there are three ways to do it. Palantir runs AIP Bootcamps that take a team from nothing to a working use case in one to five days. Palantir also offers short pilot deployments ahead of a full contract. The third route is a proof of value built by an implementation team on a Foundry environment that team already operates. That is how BD Emerson works as part of Andersen Consulting: the first use case is built on Andersen Consulting's Foundry instance, and you license Foundry only when the result justifies moving it to production. The right route depends on how much evidence your finance and risk committees need before they approve a multi-year platform.

Why does a Palantir proof of value come before the license?

Foundry is an operating platform, and its cost is justified by the decisions it improves, which nobody can see in a demo on sample data. A proof of value answers three questions that a sales cycle cannot: whether your source systems give up their data cleanly, whether the people who make the decision will use the application, and whether the measured gain is large enough to pay for the platform. Our article on what Palantir costs covers the license side of that equation. The proof of value supplies the other side, a number from your own operation.

Palantir built its own sales motion around this idea. Its annual report for fiscal 2024 says the company introduced AIP bootcamps during 2023 to deliver real workflows on actual customer data in days. The method works because a working application on real data settles arguments that slides prolong.

What is a Palantir AIP Bootcamp?

An AIP Bootcamp is a hands-on workshop run by Palantir. The bootcamp page describes going from zero to a use case in five days, and Palantir's own account of how bootcamps work puts the range at one to five days, with participants building on their own data and their own use cases. A bootcamp is the fastest way to see the platform do something with your data, and it costs your team a few days.

A bootcamp has limits that matter to an approval committee. It is short, so the use case is narrow by design. It shows that the platform can do the job. Production data volumes, access controls, a full shift of real users, and a business result measured over time are outside what five days can cover. Treat a bootcamp as the answer to "can Foundry do this?" and plan a longer exercise to answer "is it worth it?"

How is a pilot different from a proof of value?

A pilot tests whether the software works in your environment. A proof of value tests whether a specific business result moves. The difference shows up in how each one ends. A pilot ends with a working system and a renewal conversation. A proof of value ends with a measured number against a target that was agreed before the build started, such as approval cycle time, unplanned downtime, or minutes per staffing decision.

That agreed metric is the piece most often skipped. Our article on why AI pilots stall describes what happens without it: the pilot works, nobody can say what it is worth, and the budget goes elsewhere.

How does a proof of value on Andersen's Foundry instance work?

BD Emerson is part of Andersen Consulting, and Andersen Consulting operates its own Foundry and AIP environment. That lets us run the proof of value in four steps, with a platform license needed only at the last one.

Three practical consequences follow. Platform procurement stops being the first step, which takes the procurement wait off the front of the project. The build happens in a production instance, so the ontology, pipelines, and security model are built the way they will run later. And the license decision is made with a result in hand.

The engagements in our case studies ran on this kind of timeline. A contract workflow connecting SAP and Coupa reached deployment readiness in about four weeks, and a workforce allocation system went from kickoff to production at pilot sites in eight weeks.

Who builds the proof of value?

A proof of value needs a small team for a short time. A deployment strategist owns the business problem, the metric, and the relationship with the executive sponsor. Forward deployed engineers design the ontology, build the pipelines from your source systems, and build the application and any AIP agents. A data engineer handles source extracts, dataset quality checks, and pipeline builds. On our teams the deployment strategist typically brings 12 to 15 years of industry experience with eight or more on Foundry and AIP, lead forward deployed engineers bring five or more years on the platform, and every engineer works in Python, TypeScript, or Java. The people who build the proof of value should be the people who take it to production, because the handoff between a demo team and a delivery team is where context gets lost.

What moves when you go from the proof of value to your own license?

A proof of value built in someone else's environment is only useful if it can move. Foundry is designed for that. Foundry DevOps packages any combination of Foundry resources, such as pipelines, ontology definitions, and applications, as a product with version and dependency management, which is the mechanism for installing a build somewhere other than where it was made. Data connections are re-pointed at your sources from your own environment, and access controls are rebuilt on your identity groups.

Two things should be agreed before the build starts. The first is data handling: what data enters the environment, who can see it, how long it stays, and how it is deleted afterward. The second is ownership: the ontology design, pipeline code, and application built for you should transfer to you with the migration. Ask for both in writing.

What should you ask before any Palantir proof of value?

These questions apply whether Palantir, another firm, or BD Emerson runs the exercise.

• Which single metric defines success, what is its baseline today, and who signs off on the measurement?
• Is the build running on live connections to source systems or on an extract, and who has approved the data leaving its home system?
• Who are the real users during the test, and how many shifts or cycles will they run it?
• What happens to the build if you decide against a license, and do you keep the design documents and findings?
• What does production cost, including platform license, compute, and the engineering to expand, and who has seen that number?

The last question is where outcome-linked pricing helps. Andersen Consulting can link fees to delivered results, so the cost of the engineering tracks the value the use case produces.

Who should run it?

A bootcamp with Palantir is the right start when the open question is technical and the team wants to learn the platform. A proof of value on a consultancy's environment fits when the open question is financial, when platform procurement would otherwise delay the start, or when the organization wants an implementation team that will stay through production. The two combine well: a bootcamp to pick the use case, then a proof of value to measure it.

BD Emerson is an implementation consultancy and part of Andersen Consulting. We are a separate company from Palantir, and your production license is a contract between you and Palantir. If you want a use case measured on your own data before that contract is signed, our Palantir consulting team can scope the proof of value with you.