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AI Integration

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Articles

AI Integration · 7 min read

RAG vs fine-tuning — which does your AI feature actually need?

RAG and fine-tuning are the two ways to make a general-purpose model work for your case, and teams treat the choice as a fight. It is not one. RAG gives the model the right information at answer time; fine-tuning changes how the model behaves. They solve different problems — and most features need one far more than the other.

By vikas 25 May 2026

AI Integration · 7 min read

What is a vector database — and does your product need one?

A vector database stores text as numerical embeddings and finds items by meaning rather than by matching keywords. If your AI feature needs to answer from your own content, you almost certainly need one. Here is what it does, where it fits, and what your real options are.

By vikas 25 May 2026

AI Integration · 7 min read

Why your AI feature gives wrong answers — and how to stop it

When an AI feature gives a wrong answer in production, the cause is rarely the model being dumb. It is almost always one of five fixable engineering gaps. Here is how to find which one you have — and how to fix it.

By vikas 25 May 2026