
Hey, Jose here 👋. Co-founder of imglab, a service for image processing and optimization on-demand.
We have recently launched the cloud version of our previous on-premises service, which was already used by some customers on production.
Our pricing philosophy is to charge in a monthly basis for unique master images. That means that if you have 1000 master images stored on S3 it doesn't matters if you ask for 5000 transformations of those 1000 images, we will charge at the end of the month a maximum of 1000 master images.
All plans include too:
Before continue, if you want, you can take a better look to our pricing page: https://imglab.io/pricing
And we have 4 different plans:
An image source is a data source where master images are located, currently supporting Amazon S3, Microsoft Azure Storage, Google Cloud Storage, a Web Path or a Web Proxy URL.
We believe that the prices are fair and competitive, but we really appreciate any feedback, ideas or improvements that can make these plans more attractive to customers (or even to you!, if you are thinking into improving your web images).
I'm more than happy to answer any other related question.
Thanks.
I'm not entirely sure what your service does (img processing/transforming for ML?), but a basic design principle is to avoid providing more than 3 options. As more pricing tiers are introduced it gives the user more to contemplate, creating more friction in the buying process and decreasing conversion.
Hi Brandon, the purpose of our service is to allow business to transform and optimize images on-demand. For example generating different versions of the same image for different devices, screen sizes, formats, etc.
You're more than right about providing less options so the customer doesn't need to think a lot about which one is the right choice. At the beginning we were thinking into use only three different plans but finally we created a cheaper one (On-Demand Plan) for those users that want to explore the service without spending a lot of money.
We take note of you feedback. Thank you very much.