Large language models (LLMs) have pushed the boundaries of what’s possible in AI. But most enterprises don’t have the infrastructure to support LLM-based agents and applications at production scale.
That’s where small language models (SLMs) and retrieval-augmented fine-tuning (RAFT) come in.
In this whitepaper, you’ll learn how SLMs fine-tuned by RAFT are turning the promises made, but unfulfilled, by LLMs into reality. You’ll also see how this new architectural approach is driving:
- 565% total cost of ownership reduction
- 92% infrastructure cost reduction
- 12.8x latency improvement
- 90% hallucination reduction