BRQ and Quod build a Multi-Agent Platform on AWS

In a highly regulated environment driven by sensitive data, the platform's evolution had to meet strict requirements for security, privacy, traceability, governance and scalability.

The challenge was to integrate generative AI into existing systems without rewriting the technology base already in place.

The architecture needed to let specialized agents interpret natural-language requests, call APIs, access knowledge bases, route flows and support operational journeys in a secure, standardized way.

There was also a strategic need: to prevent each new agent from being developed as an isolated solution.

To scale GenAI consistently, a common foundation for engineering, integration and governance was required, ready to accelerate new use cases without compromising control, technical quality and compliance with a regulated environment.

BRQ designed the architecture of Quod's Multi-Agent Platform, combining experience in AI agent solutions, knowledge of regulated environments and command of technologies across the AWS ecosystem.

Designed to create, publish, orchestrate and expose specialized agents to different consumption channels, the solution allows an agent to be triggered within Quod Studio and be ready for integration with other digital environments, such as Teams, Slack or new interfaces defined by the company.

At its technology core, the platform uses AWS resources, including Bedrock Agent Core to build and operate the agents.

The architecture includes MCP Servers, expanding integration with internal and external systems and new data sources.

BRQ was responsible for structuring the orchestration layer that interprets requests, routes each interaction to the right agent, connects flows, applies prompt standards and supports the technical and governance models defined for the platform.

In the first set connected to Quod Studio, agents were built to support queries about products, requests and tracking of statistical validations, custom demands, analyses related to attributes and data, as well as lookups of previous tickets and requests.

In practice, these capabilities turn interactions that used to depend on navigation and specific flows into journeys driven by natural language, connected to existing systems and processes.

With the Multi-Agent Platform built in partnership with BRQ, Quod created a technology foundation to expand the use of GenAI across its operation, with greater consistency, security and capacity to scale. The initiative turned Quod Studio into the first use case of this architecture, enabling specialized agents connected to existing flows, systems and data.

From this foundation, new verticalized use cases can be structured in a few days, with the potential to reuse the architecture, integrations, technical standards and governance mechanisms already in place. In the first cycle, the platform enabled several agents and capabilities, creating a common base for new AI applications.

For Quod, this reduces dependence on isolated initiatives and strengthens a corporate approach to scaling agents with security, standardization and compliance with a regulated environment. With this foundation, new fronts such as credit, collections, risk and anti-fraud can be connected to the same architecture, leveraging the structure already in place to accelerate the evolution of the company's GenAI strategy.