Pay-per-use pricing is a pricing model where users only pay for the exact amount of usage they require, rather than paying a fixed fee for access to a product. With pay-per-use pricing, users can access a product and only pay for the amount they use, which can make the product more accessible and affordable.

There are several benefits of using pay-per-use pricing for AI products, including:

Affordability: Pay-per-use pricing enables users to pay only for what they need, avoiding the financial burden of upfront costs and allowing greater flexibility to adjust their usage as needed. This can make AI products more accessible and appealing to a wider range of potential customers.

Flexibility: Pay-per-use pricing enables users to access AI products on a flexible and scalable basis, depending on their specific needs and usage patterns. This can help increase usage and adoption of the product, while also reducing the risk of unused capacity and wasted resources.

Transparency: Pay-per-use pricing provides greater transparency and clarity around the actual costs of using an AI product, helping users to better understand and manage their spending. This can also help product creators to more accurately reflect the value of their product and better align pricing with customer demand.

Accuracy: Pay-per-use pricing enables product creators to more accurately track and monetize usage of their product, providing a more accurate reflection of its true value. This can help increase revenue and profitability, while also providing better insights into customer demand and usage patterns.

A wide range of AI products can benefit from pay-per-use pricing with Crumb. Some examples include:

AI-powered analytics and reporting tools: These products often require significant computational resources and may have variable usage patterns depending on the needs of the user.

AI-powered chatbots and virtual assistants: These products may have usage patterns that vary depending on the season, time of day, or specific customer interactions.

AI-powered image and video analysis tools: These products may have usage patterns that vary depending on the number and size of the images or videos being analyzed.

AI-powered language processing tools: These products may have usage patterns that vary depending on the length and complexity of the text being analyzed.

AI-powered recommendation engines: These products may have usage patterns that vary depending on the number and type of recommendations being generated.