Engineering Architecture: The Orchestration Layer

The industry-standard chat interface is frequently an inefficient way to handle professional tasks. It places the burden of work on the user, requiring them to figure out how to extract value through trial-and-error prompting. Our engineering focus is on the Orchestration Layer—the internal logic that translates a user’s high-level intent into a structured, finished result without the back-and-forth friction.

Scaling a production-grade system requires a departure from basic retrieval methods. Most out-of-the-box setups struggle with accuracy because they rely on simple mathematical similarity. To fix this, we look at multi-stage retrieval pipelines. This often involves a broad search to find potential data points, followed by a more intensive ranking process to ensure the information fed into the system is contextually relevant to the specific problem at hand.

We are increasingly moving toward Agentic Workflows. In this setup, the system decomposes a single request into a series of logical sub-tasks. It can then interact with external data stores or specialized tools autonomously to fetch exactly what it needs for each step. The primary engineering challenge here is managing Non-Deterministic Latency—the reality that complex reasoning takes time. By exposing the agent’s progress to the user in real-time, we provide a clearer mental model of the work being performed, which improves both the user experience and the overall reliability of the system.