Citra Ecosystem

How Citra Works

Citra connects artists, developers, and image users through creator-approved image records, model training, generated image certificates, and transparent usage reports.

Citra Rights + Revenue Layer
Artists Upload images
Developers Train models
Users Generate images
Records Track usage
01 Image Rights

Images enter Citra with rights status, review state, and owner records.

02 Model Lineage

Training connects models back to the images and permissions used to create them.

03 Usage Reports

Artists can see where approved images are used and how revenue is recorded.

04 Certificates

Generated outputs can include a public certificate for provenance checking.

The Trust Loop

Creative work moves through records

Citra is designed so each role can understand what happened: who contributed an image, which model used it, what was generated, and how creators are credited through platform records.

1

Artists contribute assets

Image owners upload work, choose rights settings, and can review permission-required usage.

2

Citra records consent

Rights, approvals, permission grants, and usage activity become part of the platform record.

3

Developers train LoRA models

Developers prepare workspace datasets, set training parameters, and publish trained models.

4

Users generate images

End users generate through published models and can download generated image certificates.

5

Creator value is tracked

Wallet records, model earnings, and image usage reports help creators see how their work contributes.

Three Roles, One System

Each participant sees a different doorway into the same platform.

For Artists

Upload work and understand how it is used.

Artists and image owners can upload assets, choose rights categories, receive permission requests, and review usage reports for models and generated revenue.

  • Artist verification and image review
  • Free to Use, Standard, and Permission Required flows
  • Usage reports and owner earnings records

For Developers

Build models from workspace datasets.

Developers keep approved images, prepare captions, submit LoRA training jobs, publish models, set generation pricing, and receive model earnings through wallet records.

  • Citra Image Library and project workspace
  • Caption files, training status, and model publisher
  • Pricing, generation, and model earnings records

For Users

Generate images with clearer provenance.

Users browse published models, generate images, download outputs, and keep a certificate that links the output back to Citra's model and rights records.

  • Model discovery and image generation
  • Wallet credits for generation
  • Generated Image Certificate for verification

Revenue Sharing

Creator earnings follow the records.

When a generation succeeds, Citra records the model used, the model price, and the image records connected to that model. Those records determine which creator accounts receive platform-tracked earnings.

01

Baseline split

Each successful generation starts from the model price: 45% model/developer pool, 40% image-owner pool, and 15% Citra.

02

Developer earnings

Generation cost is deducted from the 45% model/developer pool before the remaining developer-side earnings are paid.

03

Image owner share

Standard images share the 40% image-owner pool by training-image records and share weights.

04

Usage reports

Image owners can see which models used their images and what platform-tracked earnings were recorded.

See the current calculation rules
Model/developer pool: 45%

Citra deducts the estimated generation cost from this pool. The remaining amount goes to the model owner and any parent-model lineage: 70% main model, 15% first parent, 10% second parent, and 5% third parent. If a parent layer does not exist, that share rolls back to the main model owner.

Image-owner pool: 40%

Standard training images share this pool. Free to Use images do not receive an image-owner share by default. Permission Required image-owner share is delegated to the developer side, because compensation or usage terms must be arranged directly between the image owner and developer.

Citra platform share: 15%

This platform share is recorded separately from creator earnings. If no chargeable image-owner pool is available, the unused image-owner pool is reallocated: 75% to the developer pool and 25% to Citra.

Image rights change the calculation. Free to Use images do not create an image-owner share by default. Permission Required image-owner share is assigned to the developer side and handled by direct terms between the image owner and developer, while Citra keeps the approval and usage trail visible.

Trust Infrastructure

The visible product is simple. The records underneath make trust possible.

Citra does not only store images and models. It keeps platform records that make the ecosystem easier to audit, explain, and improve as creator permissions, training, and generated outputs grow.

Rights Ledger Permission and status history for uploaded images.
Training Snapshot Dataset, caption, base model, and parameter records for training.
Usage Report Image-level view of model usage, permissions, lineage, and earnings.
Generated Certificate Public verification page for generated images created through Citra.

How To Use Citra

Quick role-based starting points.

Generate an image as a user

Open Models, choose a published model, add your prompt, generate, then download the image or certificate.

Upload an image as an artist

Open Image Uploaded, submit the image, choose rights status, add tags, and wait for admin review.

Use a permission-required image

Request permission from the image page, enter the owner code if required, then keep the image in your workspace.

Prepare a training dataset

Keep images into Citra Image Library, copy them into a project folder, generate or edit captions, then submit LoRA training.

Publish a trained model

Select your trained model file, add model information and tags, generate example images, choose a thumbnail, set price, and publish.

Ready to explore?

Help ensure that creativity thrives in the age of AI.