Generative AI platform powered by AWS Bedrock to accelerate the development of personalized solutions with governance and scale.

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What is Fusion BRQ?

Fusion BRQ is the platform that connects the market's leading AIs to create hyper-personalized and secure solutions, accelerating the adoption of Generative AI in businesses with greater governance, efficiency, and speed of development.

Leader in Generative AI in Brazil by ISG Provider Lens™ 2025

AWS-certified and available on the marketplace

Generative AI that delivers real business results

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Results BRQ delivered for Santander with Generative AI

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Plug & play solutions from Fusion BRQ by AWS

Fusion Studio

Secure Generative AI chat, ideal for boosting the productivity of operational teams. It allows for interaction with multiple documents simultaneously, extracting information at high speed with natural, human-like language.

Fusion Squad

Creation of squads composed of specialized hyper-agents. Each agent executes a specific stage of the development process—such as story building, interface design, requirements analysis, coding, and testing—until the final product is delivered.

Fusion UI

A set of 7 exclusive solutions focused on design and user experience (UX). It uses AI to accelerate interface creation, generate visual variations, consistently apply Design Systems, and build functional prototypes with agility.

Legacy Modernization

Accelerates the modernization of legacy systems with AI support. It identifies reusable components, converts legacy code into modern languages, and generates automated documentation, facilitating the transition to more current architectures.

Fusion Governance

Manages AI usage on a per-project basis. It monitors costs, controls access, and tracks request volume and consumption by language. Ideal for ensuring governance and financial control in the use of Generative AI at scale.

Fusion Review

Focused on sentiment analysis and user feedback. It is used to extract insights from reviews on platforms like the Play Store, identifying patterns of dissatisfaction, praise, and opportunities for digital product improvement based on user comments.

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