5 docs tagged with "Large Language Models (LLM)"

In this recipe, we use product data and customer segment information to create tailored product descriptions with an LLM (OpenAI). The challenge is that customers with varying priorities view the same products, and using a single generic description may fail to engage or resonate with different segments.

Conscia Recipes are designed to be intentionally open-ended, providing a robust starting point for building custom workflows. However, just as Components can come togther to form more complex Flows or populate bespoke experiences, Recipes can be built using others as a foundation.

This recipe demonstrates the procedural orchestration of three different targeted applications of LLM technology using an LLM "master router". Designed in a chat-bot context, executing this recipe grants the business user a framework for a comprehensive automated support solution using Conscia, with opportunities for capability expansion and levers available for tuning and manipulation. While a human customer service agent is superior at responding to a customer's mood and responding appropriately, LLM-based interfaces can still lean in that direction; the more comprehensively they do so, the fewer support requests need to be served by a human agent.

This recipe demonstrates the manual orchestration of three different LLM product recommendation models. Executing this recipe grants the business user the decision-making power to determine in which circumstances each recommendation model should be used.

A lightweight, task-specific microservice can extend the capabilities of Conscia's low-code platform tremendously, and allow for a streamlined and clear business user experience despite complex programmed functions being executed in the workflow. This recipe demonstrates one such microservice.