You Spent $35,000 Fine-Tuning a Model. A $28,000 RAG System Would Have Done It Better.

Short summary

Many enterprise teams overspend on fine-tuning when RAG (retrieval-augmented generation) solves 80-90% of the problem at lower cost and faster deployment. RAG reaches production in 4-8 weeks for ~$28k versus 3-6 months and $35k+ for fine-tuning. Start with RAG, measure accuracy, and add fine-tuning only for behavior problems that retrieval alone cannot fix.

• •RAG solves 80-90% of problems teams plan to fine-tune for, at lower cost ($28k vs $35k+)
• •RAG reaches production in 4-8 weeks; fine-tuning takes 3-6 months
• •Architecture sequence: start with high-quality retrieval (chunking, vector DB, re-ranking), then add fine-tuning for remaining behavior issues

Generated with AI, which can make mistakes.