LLM-as-translator pattern: Adding natural language understanding to an existing system without rewriting it

But as technology advances, new innovations arise that those companies will want to leverage.

Take conversational search.

With the growing prevalence of LLMs, many consumers now expect the ability to have a natural-language conversation with search capabilities to help them find what they’re looking for, refining results along the way.

However, most retailers already have search capabilities, often keyword-based, that work from existing catalogs.

Often, these platforms support the rest of the business by providing APIs, which make them approachable and easy to use.

The first instinct may be to replace those legacy systems, but modernizing the implementation can be expensive and disruptive to the business.

One approach is to introduce an abstraction layer that enables a modern façade over an existing implementation.

Rather than replacing the system, this layer translates the request into something that the system understands.

While the use case discussed here is a search capability, this approach can be applied to any system that requires structured input.

Core principle …