diff --git a/README.md b/README.md
index 0ec4ce7..58f505e 100644
--- a/README.md
+++ b/README.md
@@ -88,7 +88,7 @@ Developed by BRIA AI, RMBG v2.0 is available as a source-available model for non
 
 Bria RMBG2.0 is availabe everywhere you build, either as source-code and weights, ComfyUI nodes or API endpoints.
 
-- **Purchase:** To purchase a commercial license for RMBG V2.0 **or** an API package [Click Here](https://bria.ai/contact-us).
+- **Purchase:** To purchase a commercial license for RMBG V2.0 **or** an API package [Click Here](https://share-eu1.hsforms.com/2sj9FVZTGSFmFRibDLhr_ZAf4e04).
 - **API Endpoint**: [Bria.ai](https://docs.bria.ai/image-editing/v2-endpoints/background-remove), [fal.ai](https://fal.ai/models/fal-ai/bria/background/remove), [Replicate](https://replicate.com/bria/remove-background)
 - **ComfyUI**: [Use it in workflows](https://github.com/Bria-AI/ComfyUI-BRIA-API)
 - **GitHub**: [github.com/Bria-AI/RMBG-2.0](https://github.com/Bria-AI/RMBG-2.0)
@@ -111,7 +111,7 @@ Join our [Discord community](https://discord.gg/Nxe9YW9zHS) for more information
 - **Model type:** Background Removal 
 - **License:** [Creative Commons Attribution–Non-Commercial (CC BY-NC 4.0)](https://creativecommons.org/licenses/by-nc/4.0/deed.en)
   - The model is released under a CC BY-NC 4.0 license for non-commercial use.
-  - Commercial use is subject to a commercial agreement with BRIA. Available [here](https://bria.ai/contact-us)
+  - Commercial use is subject to a commercial agreement with BRIA. Available [here](https://share-eu1.hsforms.com/2sj9FVZTGSFmFRibDLhr_ZAf4e04)
 
 
 - **Model Description:** BRIA RMBG-2.0 is a dichotomous image segmentation model trained exclusively on a professional-grade dataset. The model output includes a single-channel 8-bit grayscale alpha matte, where each pixel value indicates the opacity level of the corresponding pixel in the original image. This non-binary output approach offers developers the flexibility to define custom thresholds for foreground-background separation, catering to varied use cases requirements and enhancing integration into complex pipelines.