White-label AI: offering your own AI to your customers

What is white-label AI and how does it work?

White-label AI is software or AI technology that a provider develops and allows another company to offer under its own brand [1]. In practice, it is a ready-to-use tool that the reseller customizes to its identity and sells as its own offering [4][23].

The general principle of white labeling is not specific to AI: it is a product or service designed by a third party, which is then personalized and resold under the reseller's brand [25].

The roles are divided by a license. The provider builds the product and then licenses it to the company that sells it [15]. Three elements remain with the provider:

• the core platform;
• the code;
• the infrastructure [15].

The provider remains invisible to the end customer. The AI partner works behind the brand of the company that holds the commercial relationship [9]. A white-label chatbot, for example, is configured and billed under its own brand, without the customer seeing the provider [3].

A note on this file: these definitions come mainly from publishers and aggregators that sell this type of solution. They describe the mechanism well, but they do not replace reading the license agreement, which sets the actual scope of what the reseller can customize and charge for.

Which AI solutions can be offered under one's own brand, and who is this model for?

AI solutions that can be offered under one's own brand fall into five documented families. The publishers cited below are commercial players, given as examples and without ranking.

• Chatbots and conversational agents: the agency configures and bills an agent under its own brand, without its client seeing the provider [3]. BotPenguin targets agencies and technology providers [7]. Tidio offers a white-label option in its Plus and Premium plans [16]. Konverso describes fully customizable AI agents [11].
• Voice AI: AirAgent offers an AI phone switchboard available 24/7 [19], as well as a callbot [20].
• Generative AI for text and images: Brain Pod AI offers text and image generation under the reseller's brand [22]. White-label blog writing also targets agencies [23]. Samsa offers an image and video platform where clients train their own models [33].
• Prospecting: Salesforge allows resale or rebranding of its outreach platform [30].
• Multichannel platforms: Invent targets agencies, franchises, and brands [5].

Who this model is for

• Agencies: they can offer advanced services without hiring data scientists or developers [17], and increase their revenue without increasing headcount [12].
• IT services companies (ESN): they can add a custom AI service under their own brand [6].
• SaaS companies: they are also concerned by these offers [15].

What can be customized in practice, and which business models to choose?

White-label offers advertise customization that covers visual identity, domain, pricing, and collection of payments. These are claims made by publishers, to be verified in a demonstration.

What publishers announce

• Identity: Xeko claims it lets an agency offer an AI solution under its own identity, without depending on a tool displayed under a third-party brand [21][24].
• Logo, colors, domain: BotSaaS promises use of the reseller's logo, colors, and domain name, with the provider managing the AI and infrastructure [31].
• Pricing and payments: Robofy announces resale under the reseller's brand, domain, and prices, with 100% of customer payments retained [29].

The "project + license" model

According to Sider, three models dominate for white-label AI agents [14]. The first, "project + license," combines an initial implementation with a recurring license per client, per bot, or per seat [14]. It is attractive for agencies and predictable for clients. The identified risk is drift in customization [14]. A customization scope defined from the outset of the contract helps limit this risk.

The available excerpt does not detail the usage-based SaaS model or the third model. They are therefore not described here.

Oupi offers a white-label version with a custom domain.

White label, simple resale, co-delivery: what should be checked before starting?

Before starting, three points need to be verified: who actually holds the commercial relationship, under which license model, and to what extent one depends on the provider.

White label, simple resale, co-delivery. In white label, the AI partner works behind the brand of the company holding the commercial relationship [9]. White label compares to simple resale in terms of commercial autonomy [2]. Keeping the customer relationship is the argument put forward by a publisher such as Xeko [21][24]. The available excerpt of the source on co-delivery only details the white-label case [9].

Promises to be taken with caution. BotPenguin announces a personalized chatbot in 12 hours [13]. On AirAgent's website, testimonials mention a voice solution ready in 48 hours and +40% recurring revenue [20]. These figures come from publishers or from feedback published on their sites. Reddit reviews, for their part, are individual opinions [27].

Criteria to check:

• Commercial relationship: does the contract leave you in control of the customer, billing, and messaging?
• License: a recurring "project + license" model per client, bot, or seat is predictable, but exposes you to drift in customization [14].
• Dependence: the platform, code, and infrastructure remain with the provider, which grants a license [15].