Can You White Label an AI Tool and Resell It?

"White label an AI tool" describes three different businesses, and people arguing about whether it is allowed are usually arguing about different ones. Sort out which you mean and the answer becomes clear, because the terms of service treat them very differently.

• Reselling someone's product under your brand. You put your logo on their app. Usually not permitted without a specific reseller agreement.

• Building your own product on their API. You write software that calls a model, and your customers buy your software. Usually permitted, and it is the standard business model the API pricing exists to support.

• Delivering a service that uses AI internally. You do the work, AI helps you do it, the client buys an outcome. Always permitted, and it is not really white labelling at all.

Most people asking the question want the second one and have been told the answer to the first.

Model one: white label someone else's product

This is the one that gets people in trouble. Taking a vendor's application, hiding their branding, and selling access to your own customers is typically prohibited outright in consumer and business terms. The usual clauses ban sublicensing, reselling, and removing or obscuring proprietary notices.

That does not mean it is impossible. It means it needs a reseller or partner agreement, and those exist. If your plan genuinely is to resell a specific product, contact the vendor's partnerships team rather than reading the self-serve terms and hoping. The commercial terms of a real reseller agreement are usually workable, and the deal comes with the right to use the brand rather than the obligation to hide it.

What you cannot do is proceed quietly. Vendors detect this through support tickets from customers they have no record of, and the account termination lands on the day your customers need the product.

Building on the API

This is the normal path, and it is what API pricing is for. You build an application, it calls a model, your customer buys your application. You are not reselling the model any more than a restaurant resells electricity.

Four boundaries still apply on most platforms, and they are the ones worth reading carefully:

1. You cannot present the model as your own model. Building a product on someone's API and telling customers you trained it is a misrepresentation, and increasingly a regulatory problem as well as a contractual one.

2. You usually cannot pass through raw API access. A thin wrapper that just forwards prompts and returns completions starts to look like resale. Products that add real functionality do not have this problem.

3. You may have disclosure obligations. Some providers require you to disclose that AI is involved, and separately, regulation may require it regardless of what your vendor asks.

4. Usage policies flow through to your customers. If your product lets end users generate prohibited content, that is your violation, not theirs. Anthropic's usage policy is a representative example of what that flow-down looks like in practice, and every major provider publishes an equivalent.

The practical test for boundary two: if you removed the model from your product, would anything of value remain? Workflow, data, integrations, a UI someone actually wants? If the honest answer is no, you have a reselling problem and also a business problem, which is covered in the wider survey of models in AI monetization strategies.

Delivering services with AI behind them

An agency that produces market research reports faster because AI drafts them is not white labelling anything. The client is buying your judgement and your accountability. What tools you use to produce the work is generally your business, in the same way that which word processor you use is your business.

Two caveats that come up constantly. Client contracts sometimes restrict what third-party services their data may pass through, so check before pasting a client's material into anything. And whether you volunteer that AI was involved is a relationship question rather than a licensing one, discussed properly in productized AI services.

The five clauses to read before you sell anything

Open the vendor's terms and search for these. It takes fifteen minutes and it is the entire due diligence for most small products.

The last row is the one that ends businesses rather than merely annoying them. If your vendor can terminate for convenience with thirty days' notice, your entire product has a thirty-day fuse, and the only real mitigations are a second provider you have actually tested and an architecture that can switch. How to negotiate a contract with an AI vendor covers what is genuinely negotiable at small scale, which is more than most founders assume.

Pricing a product you do not control the cost of

The specific hazard of building on someone else's model is that your cost of goods can change without you doing anything. Providers cut prices often, which is pleasant, and occasionally raise them or retire the cheap model you built on, which is not.

Three habits that keep this survivable:

• Price on value, not on a margin over token cost. A margin-based price forces a customer-visible price change every time the vendor moves.

• Know your cost per customer per month, as a real number. Heavy users on a flat price are where the margin quietly goes.

• Keep a second provider integrated, not just identified. The switch is a two-day job if you built for it and a two-month job if you did not.

If you are selling this to businesses rather than developers, the buying conversation is mostly about reliability and support rather than which model is underneath, which is the pattern in how to sell AI services to local businesses. Retainer structures for ongoing work are in how to price an AI agency retainer.

Frequently asked questions

Can I say my product has "our AI" if it runs on someone else's model?

You can call the product yours. Claiming you built or trained the model when you did not is a misrepresentation, and it is the kind that surfaces during due diligence or a customer's security review at the worst possible time.

Do I have to tell customers which model I use?

Usually not contractually, and many products deliberately do not, so they can switch providers freely. Some enterprise buyers will ask directly, and refusing to answer costs you deals in regulated sectors.

Is a wrapper app a legitimate business?

It can be, if the wrapper is where the value is: workflow, domain knowledge, integrations, data. What fails is a wrapper whose only feature is a different colour scheme, and it fails commercially before it fails legally.

What happens if I breach the terms without realising?

Typically a warning and a requirement to change, rather than immediate termination, for a good-faith small business. That is a courtesy rather than a right, and it is not one to plan around when your customers depend on the service staying up.