- Industry
- Fintech
- Founded
- 2015
- Headquarters
- New York, NY, USA
- Website
- cindicator.com
- Engineering time reclaimed from image-processing maintenance
- Faster development by removing custom image scripts and workflows
- Consistent image performance across the application
Before Uploadcare, I handled all image processing myself with scripts. It was a nightmare. It’s a lot of work, and it’s not interesting work.
Sergey BliznetsovFront End Architect
Executive summary
Cindicator is a fintech platform that crowdsources predictive analytics to guide investment decisions in crypto and traditional financial markets. While the core of the product is data-driven, images play an important role across the application, from analyst profile avatars to visual assets embedded in prediction requests.
Once Uploadcare became part of the stack, image uploads, transformations, and delivery no longer required custom scripts or separate infrastructure. Responsive image generation was handled automatically, allowing the team to focus development effort on the platform itself rather than maintaining image-processing workflows.
The challenge: managing image processing without adding infrastructure complexity
Cindicator’s platform supports a large community of analysts who contribute forecasts and insights. As part of this experience, analysts upload profile images, and the application embeds images inside prediction requests distributed across the platform.
These use cases required images to be resized, transformed, and served efficiently across devices. Initially, image processing was handled manually through custom scripts that generated multiple variants for each image. Maintaining these scripts, managing folder structures, and keeping delivery logic in sync quickly became time-consuming and fragile.
As these demands grew, automating image transformations and delivery at scale became essential. Continuing to invest engineering time in custom infrastructure that wasn’t core to the product was no longer sustainable.
The solution
Cindicator introduced Uploadcare to handle image uploads, transformations, and delivery as a single, integrated workflow. Instead of pre-generating and managing image variants, transformations could be defined directly in URLs and processed on demand.
This approach removed the need for batch image processing, custom scripts, and manual coordination between storage and delivery layers. Image processing became part of the application’s normal request flow rather than a separate system to maintain.
How Uploadcare helped
- Automated image transformations via URLs: URL-based transformations replaced custom scripts and folder structures, removing repetitive maintenance work and reducing operational complexity.
- Responsive images with minimal frontend code: Developers can define the exact image size and format directly in markup, making responsive image support easier to implement and maintain.
- Integrated delivery for processed images: Images are transformed, cached, and served automatically, ensuring consistent performance for users without requiring separate processing or delivery systems.
On the front end, I really like that you can generate responsive images just by modifying the URL. You drop it into the code, and Uploadcare does everything else.
The results
Image handling moved from a collection of custom scripts and manual processes into a centralized, automated workflow that required minimal ongoing maintenance.
- Eliminated custom image-processing scripts: URL-based transformations replaced manual resizing workflows, removing repetitive maintenance tasks and reducing operational complexity.
- Simplified frontend implementation: Developers can request specific image sizes and formats directly in markup, making responsive image support easier to implement and maintain.
- Unified processing and delivery: Images are transformed, cached, and served automatically, ensuring consistent performance without coordinating separate processing and CDN systems.
On a previous project, I avoided using Uploadcare because I thought it would take more time to integrate. I regret that decision. I spent far more time maintaining my own solution.