blog/ai industry
Do You Need a Custom AI Model? LLM APIs vs Fine-Tuning vs RAG
SoftiIntel Team · · 6 min read
the short answer
Most businesses don't need their own AI model. Start with an LLM API plus good instructions; add RAG when answers must come from your own data; consider fine-tuning only for consistent style or specialised formats at high volume; and train a model from scratch only if AI is your core product and you have large proprietary data.
Option 1: LLM API with good prompts
Fastest and cheapest to start. Great for drafting, classification, extraction and summaries where general knowledge is enough.
Option 2: RAG over your data
Adds your documents at answer time — the default for chatbots and assistants that must be accurate about your business. See what is RAG.
Option 3: Fine-tuning
Teaches a model a consistent style, format or narrow task using examples. Useful at scale, but it doesn't keep knowledge current by itself — combine with RAG for facts.
Option 4: Your own model
Expensive and rarely justified for SMEs. Worth it mainly for AI-first products with unique data at scale.
How to decide
- Does the task need your private facts? → RAG.
- Does output need a very consistent format at high volume? → consider fine-tuning.
- Neither? → API with strong prompts and evaluation.
Get advice
We'll recommend the simplest option that works — tell us the use case or see AI integrations.