Enterprises experimenting with large language models (LLMs) often encounter the same challenges once pilot projects move into production. Infrastructure costs escalate rapidly, response times become unpredictable under load and outputs are difficult to audit or explain. While LLMs remain useful for exploration and prototyping, their size and generality make them difficult to operate sustainably within enterprise platforms.
A practical alternative emerging in production systems is the combination of small language models (SLMs) with
