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AI Models Customization - Your Approach
Approach - Use - What You Need - Time - Pros - Keep In Mind
Dr. Aruna Kishore Veleti
August 17, 2026
AI Architects while evaluating various approaches for AI Models customization need to consider various dimensions. This post lists some of such Model Customization Dimensions.
R | Use | What You Need | Time | Pros | Keep In Mind |
|---|---|---|---|---|---|
Prompt Engineering | Quick Guidance | Good Prompts | None | Simple, Faster | Less Control |
RAG | Knowledge Integrations | Vector DB | Moderate | Relevance, Context Engineering | Longer Prompts, More Compute |
Fine Tuning | Domain Specific | Labeled Data | High | High Precision, Custom Control | Needs Training + Compute |
Pre-Training | From Scratch | Large Datasets | Weeks, Days | Max Control | Very Resource Intensive |
Other key points:
Understand how content is selected, aggregated, surfaced
Awareness on Compliance
Voice Profile your enterprise Knowledge and Customer Data for faster lookups
Establishing Keyword searches for Enterprise AI ready datasets