Understanding the Options
When customizing AI for your organization, you have two main approaches: Retrieval-Augmented Generation (RAG) and fine-tuning. Each has distinct advantages.
RAG Approach
Advantages
- No model training required
- Knowledge updates instantly
- Can cite sources
- Lower cost
- Better for factual accuracy
Best For
- Internal knowledge bases
- Documentation Q&A
- Frequently updated information
Fine-Tuning Approach
Advantages
- Faster inference
- Better style matching
- Deeper domain adaptation
- No retrieval latency
Best For
- Specific output formats
- Domain-specific language
- High-volume, low-latency needs
Decision Framework
Choose RAG when knowledge changes frequently. Choose fine-tuning for style and format. Often, the best solution combines both.
Hybrid Strategies
Fine-tune for domain understanding, then use RAG for specific knowledge retrieval.