Bria Technology | Bria.ai
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BRIA’s Technology

We're your holistic solution for all visual generation and modification requirements, whether it's access to foundation models, APIs, SDKs or Web integration. With a commitment to safe commercial use, we empower your organization and address your business challenges at scale while offering solutions with full liability coverage.

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Quality

Exclusively trained from scratch on the largest licensed dataset built in collaboration with our data partners we guarantee the best quality outputs.

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Legal & Safe

Trained on fully licensed data, we guarantee quality outputs with full liability, copyright protection, privacy and non-harmful content ensuring safe commercial use.

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Use It Your Way
Our technology is licensed and can be used for commercial use.

Licensed Source Models

Full suite of licensed models (source and weights) ready for use or fine-tuning, along with a comprehensive toolkit. Enhancing the research process by gaining flexibility, velocity and scale.

API’s Pipeline

Enhance your product with Generative AI capabilities by utilizing BRIA’s API and SDK for the quickest time to market. Allow your users to generate and customize real and synthetic visuals.

We built a machine that creates the largest licensed high quality visual collection in the world.

Our proprietary attribution engine: Our patented attribution engine rewards data contributors and creators based on their visual impact on every visual generation, thus nurturing a sustainable economy.

Algorithm Family Models

BRIA 2.X

High resolution images and quality outcomes

BRIA 1.4

Best in class seamless integration of text-to-image, inpainting and outpainting models

BRIA 1.2

Full compatible replacement for Stability v1.5

Brand Protector

Set of API's to monitor brand & style compliance

Generative Search

Search capabilities for any visual repository without the need for tagging or metadata

Predictable and Controllable API Pipelines 

By delayering the visual to 5 elements, we allow customization of each layer in our APIs

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Safe and Compliant Technology

Being trained on safe, fully-licensed images, the model is your fast track to generation business impact, responsibly. Using them will save you time, workload and garnet you with velocity and scale. 

Bria’s licensed source model

An existing open-source model

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Logos & Trademarks Safe

Not trained on trademarks or logos (e.g., logos of Apple, Coca-Cola or Nike), the model does not generate visuals that violate trademarks or logos.

Bria’s licensed source model

Apple on a wooden desk

An existing open-source model

Apple on a wooden desk

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Copyrights Safe

Not trained on copyright-protected or fictional-characters visuals (e.g., Yoda, Superman, or Super Mario), the model does not generate images that violate copyrights.

Bria’s licensed source model

Chewbacca

An existing open-source model

Chewbacca

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Misinformation and NSFW Protected

Our model mitigates harmful and fake visuals as well as misinformation protection. Additionally, our images are marked as AI-generated

Bria’s licensed source model

Prince singer

An existing open-source model

Prince singer

Seamless Swap-In for Higher Quality

Version Bria 2.X was built to replace SDXL.

BRIA 2.X Family of Text-to-Image Models

To counter legal and business risks for businesses and users, including copyright violations and privacy concerns, Bria has developed the Bria 2.3 text-to-image foundation model, ensuring 100% safe and ethically responsible AI for commercial use. Built on the widely respected latent diffusion architecture, similar to Stable Diffusion XL, Bria 2.3 enhances compatibility with common open-source and community standards. Its seamless plug-and-play integration facilitates the addition of extensions and pipelines, simplifying the adoption process.

The Bria 2.3 model incorporates dual text encoders, a VAE, and a UNet backbone, making it ideal for research teams to easily retrain and fine-tune with proprietary data. It transforms images into editable latent representations and integrates textual data with visual outputs using cross-attention in the UNet. This architecture ensures that the final images not only meet but exceed quality expectations by closely aligning with the input text, optimizing for precise similarity between the added noise and the model’s predictions.

Bria 2.3

SDXL

Vs.

Prompt: Mountain

Vs.

Prompt: Burger

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