Architecture

The Rox Agent Swarm operates as the central processing unit, bridging the System of Record (SOR) and Systems of Engagement. Its primary role is to execute both system and user-driven actions. Each Agent within the Swarm is contextually scoped to a single sales representative and account pair, ensuring interactions are focused and highly personalized.

The Swarm consists of three key architectural components:

1. Natural Language Interface: Captures user intent by determining what tasks should be completed.

2. Reasoning Pathways: Plans and executes tasks by determining how to complete them effectively.

3. Evaluation and Self-improvement: Aligns agent outputs and continuously improves performance.

Natural Language Interface — Capturing User Intent

The Natural Language Interface serves as an intuitive and user-friendly medium for users to interact with the Agent Swarm. The Swarm is designed to efficiently comprehend, process, and respond to both text and voice inputs. The primary challenge lies in translating potentially ambiguous or underspecified queries into well-defined tasks that the Agents can execute. This is achieved through advanced natural language processing techniques, such as intent recognition, entity extraction, and context understanding, which enable the Swarm to accurately interpret user requirements and map them to actionable tasks.

Reasoning Pathways — Planning & Executing Tasks

The Reasoning Modules consist of four core components: task reasoning, context management, planning, and execution. The reasoning component employs sophisticated algorithms to decompose complex tasks into a series of more manageable and atomic actions. The context manager retrieves the relevant pieces of organization, seller and account level data needed to complete the task. The planning component identifies the essential set of "Rox Tools" required to accomplish each action. These tools empower the agents to perform a wide array of domain-specific actions typically carried out by sales representatives, leveraging both public and private data sources. During the execution phase, the selected tools are orchestrated in the optimal sequence to ensure efficient and effective task completion.

Evaluation & Self Improvement — Monitoring Performance & Aligning Outputs

The Agent Evaluation System is a robust framework that facilitates continuous benchmarking, monitoring, and optimization of the Rox Agent's performance. It supports real-time and retrospective evaluation, provides an interface for data labeling, and incorporates feedback mechanisms to drive iterative improvements.The self-improvement capabilities of the Agent Evaluation System are designed to align the Agent's outputs with the desired outcomes, ensuring that the Rox Agent consistently delivers high-quality results that meet the specific needs of each sales representative and account pair.